Satya Nadella - CEO of Microsoft | In Good Company | Podcast | Norges Bank Investment Management

Hi there, I've just had the most incredible experience of my life, having been allowed to interview Satya Nadella, the CEO of Microsoft, which is now the most valuable company in the world. Wow. Please tune in. Satya, you are the CEO of the most valuable company in the world. What's on your mind these days? Look, to me, Nikolai, first of all, it's great to be with you and have this conversation. What's top of mind for me is twofold, right? One is, I'm grounded in the fact that in our business, in tech business, now this is my 32nd year at Microsoft, I know that for a fact, there's no such thing as a franchise value. And so that means every day you have to get up and hopefully you're doing things that are going to be relevant tomorrow. And so to me, that's sort of perhaps the biggest lesson learned over all these decades and years. And so here we are on what is essentially a complete new platform shift that we are in the midst of. I kind of say it's my 32nd year, but it's year two of my fourth platform shift. And so what's on mind is, OK, what is this platform shift really all about? And as a company, can we be all in and innovate? I mean, at the end of the day, when I say there's no franchise value, it also means that you get to play for it all up again. Even the battles we won and the battles we lost are all up for grab again. And so therefore, there's a freshness to it. So what's on my mind is, you know, that ability to ground myself back yet on another platform shift. And it's exciting. The fact that there is no franchise value, does that make you nervous? Absolutely. I mean, it should make every one of us nervous, right? At least that's why the tech is so exciting. It's kind of like the two sides to the same coin, right? One is you're nervous and it's exciting, so therefore you can't rest. But at the same time, hey, who wants to be in a business where you don't get to reinvent yourself again and again? Absolutely. Do you think we look at tech in too narrow a sense? I mean, how can technology really be a driver for the next level of economic growth? That's a great, great question. I think a lot about that, which is, in some sense, if you think at a GDP level, tech spend, narrowly defined, is probably 4-5%. So the question is, what is happening with the other 95%? So one of the ways I've always thought about the prospects of any new technological paradigm or platform shift, like take AI. If AI is going to be the next big general purpose technology, for me, the real opportunity is, let's say tech spend goes from 5-10% over the next five years or what have you, or 10 years. Then what happens to the other 90% and the pie, does it become bigger, right? Do we have a breakthrough in healthcare driven by AI? Do we have a breakthrough in material science and energy transition because of AI? And the list goes on, right? So to me, that is fundamentally the way I think about it. I think that one of the things that might be most important for us is to consider how a general purpose technology, somebody was telling me this, right, which is in the height of the Industrial Revolution, in the United Kingdom, they spent 10% of their GDP building the railroads. And obviously, the railroads is not about the railroads, it's about the entire economy of the United Kingdom. And so something like that, I think, is what, that's the unit of analysis, at least for me, as to how tech and its future will impact the broader society and economy. Now, Google had almost all the top AI people, and you suddenly got ahead, partly due to your partnership with OpenAI. Now, how did that come about? I mean, to me, the way I came at this, Nikolai, is just very simple, which is obviously we've been like, I think the very first thing Microsoft Research did in 1995, when it was formed, was some stuff around speech, right? In fact, I think we hired a bunch of folks from CMU. And so we've been at this AI thing in its variety of different forms forever. And so one of the things that when I met with the OpenAI folks and Sam and Greg and crew back in, you know, I would say when they were working even on the Dota 2 contest and what have you, was to sort of say, wow, they have a new different approach to things. And we wanted a partner. You know, one of the things that I've always looked at over my years at Microsoft is look for high ambition technology innovation companies, right? And partnership, like whether it's Intel and Windows came together and that was successful. SAP and SQL Server came together and was successful. So I'm always looking for partners that we can innovate with. And that's what I found in Sam and team. And, you know, at that time, it was not like it was a real shot in the dark, right? It is not like, oh, wow, this is a sure thing. Everybody now talks about it as if, you know, this is the issue with tech, right? Which is long before it's conventional wisdom, you have to be all in and hope it works. And this is one of those things where we backed it long before it was conventional wisdom. And here we are. But I don't think, you know, like there's going to be severe amount of competition. You know, Google is a very competent company and obviously they have both the talent and the compute. And they have, you know, they're the vertically integrated player in this, right? They have everything from data to silicon to models to products and distribution and there's others as well. And so, yeah, we will have a significant amount of competition. And I think if anything, Microsoft's partnership with OpenAI is bringing more competition to otherwise what would have been a default. Google should be the default winner. And if we partner well and we innovate well, we can bring some competition to that. So if you look three to five years from now, where is Microsoft in this whole AI ecosystem, you think? So to me, I think about this in the fullness of the stack, right? So I want us to have, first and foremost, the best AI infrastructure. So that means when it comes to Azure, whether it's for training, whether it's for inference, to have fantastic infrastructure. We'll partner with NVIDIA. We'll partner with AMD. We'll have our own silicon. We will have our own system architecture. We will take the best system architecture innovation from Jensen and Lisa and others who may come along and make sure Azure is serving the needs of OpenAI, serving the needs of Mistral, serving the needs of PHY that we are building, right, which is the small language model. So that's kind of the first thing that we want to do, which is the best work in being able to build the infrastructure out for both training and inference. And then the next layer up, we want to have the entire data tier, right? So you can imagine, as these models and model capabilities become more capable, I think the data tier will be completely redone, right? We've talked with the retrieval augmented generation already. You have all these things, whether it's embeddings, vector search, how do you chunk data such that retrieval augmented generation can work well. So that's an entire layer. Or when context lens become bigger, that's a different sort of data layer. Like what's the throughput between data and your inference fleet? How do you sort of think about that? So therefore, we will innovate on the data layer. And then of course, on top of it is where we will innovate on our co-pilots. One of the first products we built was GitHub co-pilot. In fact, my entire confidence in this generation of AI started when I started seeing from GPT-3 to 3.5 and that implementation in GitHub. And so we now have, you know, not only GitHub co-pilot, we have co-pilot for all knowledge work in Microsoft 365. We have co-pilots for these functions, whether it's service or sales or finance. So we're going to innovate in our app layer on our own. And so that's, I think, fundamentally how I look at it. It's a full stack approach. And each layer, by the way, we will innovate. We will have partners. We will have others innovating. There will be competition even. It's not like, you know, one of the things of being a platform company is you've got to be comfortable with many third parties competing with you on different layers, because that to me is core. Otherwise, you kind of try to, you know, do everything in a monolithic way. And at least what we have learned over the years is the best thing to do is to keep each layer competitive on its own. You said in the beginning that we are year two into this paradigm shift. How do you see it compared to other technological breakthroughs that you've been through? So at least the four I've seen, Nikola, is obviously PC, client, server, both what happened on the PC and the server side. That was my first. That's kind of when I joined 92. We're at the beginning of that. Then there was the web internet, and then there was mobile cloud. And so AI is the fourth. I think one of the interesting things is each one of these built on the previous. So I don't think the web would have happened if there was not a ubiquitous PC. After all, the first time I saw Mosaic was up as a browser on top of Windows. And then Netscape came about, and then IE and what have you. And so therefore, I think you sort of see each one of these births the next. And then it goes beyond what births do. That's, I think, the real thing. And right now, we're seeing that, which is the cloud, as we know of it, and mobile and PCs on the edge have really birthed the AI age. And the question is, what happens next? Which is, does it go beyond that? And that, I think, is going to be AI that is not just about cognitive work, AI that is also going to accelerate science. So I think that that's an exciting space. AI that is going to be embodied in the real world. So what may happen in robotics is an exciting space. And so there is a bunch of things that are going to happen over time. But clearly, yes, this is year two of a complete new paradigm that obviously reinforces what happened or builds on what happened previously, but also showing early signs of what happens next. If there had been no shortage of chips now, would the development have gone even faster? That's a good question in the sense of scaling laws, right? So there are two sides to it, right? There's the training side and the inference side. On the training side, clearly, compute and compute scale and the scaling laws have proven to be very successful. And the question is, how long does that go? Is there going to be another model architecture breakthrough or what have you? I think that one has to see. It's unclear. But we definitely are not going to bet against scaling laws, nor are we going to bet against, nor are we going to say that this is the last model architecture breakthrough. In fact, a great example of it is even what we've seen even with our small language model innovation like PHY, right? Which is we are able to create what is significant capabilities in a small language model, which doesn't require, obviously, the same amount of compute, right? Which is just like attention is everything. Attention is all you need. Textbooks is all you need. I mean, that sort of intuitively speaks to how I think learning can happen. And so therefore, I would say, yes, if more capacity there is in the world, the chances are that we will be able to make progress. But at the same time, I wouldn't discount a real breakthrough in model architecture that doesn't perhaps require the same type of compute. And so that's why I think, at least I want to keep myself open-minded about it. Talking of small language models, do you think a small country like Norway should develop its own model? You know, one of the things that I've studied, there's an economist out of Dartmouth, his name is Diego Komen, and he did one of the best longitudinal studies of technology diffusion. And the fundamental conclusion, paraphrasing, was that any country that wants to get ahead should first make sure that they don't reinvent the wheel, which is they import the best general purpose technology that is available in, and then on top of it, build value add. So I think, for example, even on Norway, first thing I would do is if we feel like, for whatever reason, these foundation models are not good at Norwegian or what have you, let's make sure they're fine-tuning. And there are many things one could do even on top of foundation models, like an open AI model or a mistrial or what have you. So there are ways you can add unique knowledge, unique value on top of even what exists before you go off and say, let's build all the compute, all of it, and do the same pre-training run. You know, there's nothing stopping any country from doing any of this. But the question is, what is the value add? And so therefore, I think that you start from the value add and then back into whatever is needed for it. When you look at how important the big technology companies have become in geopolitics, what kind of reflections do you make? Well, I mean, at the end of the day, there are two things, right? One is I'm very, very grounded on the fact that we are a multinational company that is definitely, in this case, a US-based multinational company that has to earn permission and license to operate one country at a time, right? So therefore, I think of the, we're not, nation states are the ones that have power. We get to operate in any nation based on our ability to contribute to that country's progress, right? So whenever I am, whether I'm in Norway or I'm in Jakarta or New Delhi or wherever, I am always grounded on, fundamentally, the fact is, are we able to make, you know, look the local politicians and political leadership and society at large in the eyes and say that we contributed to their public sector becoming more efficient or large multinational companies in the region becoming more globally competitive because of some tech input, education outcome, health outcome, small businesses and their productivity. At the end of the day, your social contract with the country comes from your ability to contribute to their local progress. So I don't think we can ever be beyond, geopolitics will exist with or without us and our goal has to be how do you participate and have permission to operate. Moving on. In your book, Refresh, you talk about three areas. You talk about AI, you talk about quantum computing and mixed reality. So what kind of opportunities are you seeing in quantum computing? It's fascinating. In fact, I think of all those three still, right? Mixed reality, I think of it as that's an embodied AI, right? Effectively, whether it's autonomous, vehicles, robotics or people with glasses, they're all seeing, the real world is the problem, effectively. So your real world understanding, so therefore I think of in the generation of AI, some of these things become even more interesting and more important and we do need to broaden the aperture versus thinking narrowly of just one device or one form factor. Similarly, quantum is a fascinating thing. When I mentioned science, one of the things I look at it and say is in order to make progress on science, you need great in silico simulation. Quantum is the ultimate breakthrough, right? So when we have a complete new system architecture that breaks free of the Von Neumann limitation, you are then finally going to be able to simulate something like the dynamics of a cell or a molecule, right? So that I think when you can do that, then everything else even in terms of biology becomes more feasible. The interesting thing is AI is kind of like an emulator of that simulator. In other words, you can kind of simplify the search space and we see this already, Nikolai. One of the things we did recently was we have a model for material science which we use to generate a new novel compound, which we then went and manufactured. We worked with the Pacific National Lab locally here to effectively go reduce the lithium content by 70% in a new battery material and produced it, right? Not just conceptualized it, but simulated it, produced it. And so to me, something where like quantum plus AI I think can be the ultimate accelerator of science. And we are making progress. Even on quantum, we're taking a very full stack approach. We have our software stack with our Qsharp, which is our quantum programming stack. So we are excited about sort of the progress we're making on quantum and how it complements AI. And where does the gaming fit into this? Yeah, so to me, one of the things, in fact, Microsoft was in gaming long before we were into Windows. In fact, Flight Simulator, I think, was launched long before Windows was launched. So we are very, very excited, obviously, now with Activision as part of Microsoft. We have mobile gaming, we have cloud gaming, we have console gaming, PC gaming. So we are a full stack game publisher as well as a game systems provider. And so our goal there is, one, we're in gaming for our love of gaming, right? So I always sort of say we should never be in businesses as a means to some other end. Gaming is something where we want to bring joy of gaming. That's the one pure consumer entertainment category. I love the fact that gaming on a secular basis is probably going to be, if not already, the biggest entertainment category out there. So that's one. And of course it has real implications on the rest of it, right? If you think about even, remember, it's interesting. I've not talked to Jensen about it, but one of the greatest sort of successes of GPUs was fostered by innovation in gaming, right? DX, which was the Microsoft graphics stack, is what made GPUs an accelerator, right? After all, the GPUs were created for PC gaming. Gaming, I think, is both an application of AI in terms of game testing. One of the first areas I'm very excited about is games are so complicated right now. One of the things that we want to use AI is to be able to find these bugs in these even closed worlds before they're out there. And so therefore we have some very great use cases there. But beyond that, I think gaming as data in the context of some of the innovation in our models, I think is going to be important. Do you game yourself? I'm a light gamer. I used to do a lot more. Civ was my favorite game. Age of Empires is another great game that I enjoyed. I wish I could play more. But from time to time, I slip into it. You have really changed the culture at Microsoft. When you look back, what do you think are the most important changes you made? Look, I mean, Nicola, first of all, as I said, I've grown up. All my professional career as you say, I've been at Microsoft for 32 years. All the good, the bad, I was part of it. So I don't sort of somehow think that I represent all errors of Microsoft. Yeah, which makes it even more incredible that you have made these changes. Yeah. And the way, though, I came about it is quite frankly, as a consummate insider, I basically pattern matched as to, hey, when were we at our best? What was the cultural set of attributes that helped us succeed? And then when we failed, what are the cultural attributes that caused that failure? And then, you know, dampened this ladder and amplified the former. That was as simple as that. So one of the things I look back even in my career at Microsoft, when we first became the largest market cap company, I forget, I think in the early 2000s, I think we crossed G, you know, people on our campus were walking around, including me, thinking, oh, we must be God's gifts to humankind because we are so brilliant and what have you. Except what we needed to be grounded on that day was to say, wow, we now have a real responsibility to reground ourselves, to innovate again, so that we are relevant in the future, right? And so that's why I was lucky enough to have read Carol Dweck's book on mindset, which is around child psychology called Growth Mindset, and I love that book. I read it more on the context of sort of our children's education, but I must say I got educated because I felt like this is what makes individuals, children in school, it's very clear, right? It's better to be a learn-it-all versus a know-it-all, because even if the know-it-all has great innate capability, the learn-it-all, you know, will surpass the know-it-all, right? That's sort of, you know, true for children in school. It's true for CEOs in my seat. It's true for companies. And so we took that approach, Nikolai. We said, let's be a learn-it-all versus a know-it-all. And the day you say you've achieved that cultural transformation means you're a know-it-all. So therefore, it is a good way to sort of say every day you make a bunch of mistakes, you at least have the courage to acknowledge them and continue on it. And so it's not a destination you ever reach. But how do you get the organization to buy into that? How do you get it to penetrate down towards the permafrost in the organization? It's a beautiful, it's a great point. So I think the way, I think, see, the problem of corporations, especially for non-founder companies. Founders have great power and great followership, and that's why I think they're so successful, or at least we only talk about the successful founders. But if you set that class aside, for mere mortals like me, it can't be like, okay, new dogma from a new CEO and more corporate speak. It has to appeal to us as human beings. That's why I credit more of this work by Carol and team and so on. Because it's not like, I don't think anybody at Microsoft views growth mindset as a Microsoft dogma or definitely not Satya Nadella dogma. It is something that speaks to them as humans, right? Which is, it's good for them as friends, colleagues, partners, parents, neighbors. It integrates work and life. They can bring their own personality and passion to it and benefit from it. I always say, this Microsoft culture of growth mindset is not for Microsoft, it's for you. You should only practice it if you feel like it speaks to your own thriving at Microsoft and in life. That's, I think, what I attribute it to. It wouldn't have taken off if it was just another thing that is a top-down slogan. I always have believed that, which is, ultimately, people work and find meaning in work only if they can find some true, deeper meaning for themselves. That's, I think, what I've been always trying to invoke. Well, they clearly also have found true, deeper meaning in the concept of empathy because you talked a lot about that and you say that it's key to innovation and leadership and so on. Why is that? Why is it so important for you? I think about this as, I think most people think of empathy as some kind of a soft skill that's interesting in the context of your family or personal life and works all about hardcore, you know, whatever. But I look at that and say, again, where does innovation come from? Innovation comes from us being able to drive the solutions to unmet, unarticulated needs of customers out there. The key being unmet and unarticulated. That means you have to have a better sense when you're even looking at some log data or, you know, some customer interview data or whatever. It's not just the words that they're saying, but you've got to be able to walk in their shoes. And the good news there is this is innate in us all human beings. We have the ability to empathize with the other person. In fact, design thinking is that, right? So when people go and say, let's learn about design thinking, design thinking is applied empathy. And so to me, that's what I pull the thread on, which is let's not think of empathy as something that, you know, is just a soft skill that you reserve for your friends and family. But I think it's at the root of all innovation. It's about being able to meet the unmet, unarticulated needs that comes from your unique, I mean, your innate ability to have curiosity, to learn about others, walk in their shoes, innovate on their behalf. And that I think is, I think, what we have to do. And that's why I think empathy is an important, important skill for all of us. When did you first discover the power of empathy? I mean, I read your book, fantastic book. You talk very warmly about your mother, she being very empathetic. Yeah. And, you know, I think that one of the things that I, I feel like all of us learn how to turn on this bit of empathy through life's experience, right? So in some sense, every day, you get confronted with different circumstances, not just yourself personally, but people around you. For me, obviously the birth of my son, for both my wife and me, was a life-changing event. And it was something that, you know, over the years, I at least learned a lot because I remember in the early days, it was all about, sort of, my son was born with cerebral palsy, he passed away a few years ago. but, you know, when he was born, it was a lot about what happened to me. I was sort of, you know, essentially, quote-unquote, you know, all about why did this happen to us, why did it happen to me, or how, and then I realized after watching, in some sense, my wife, who was there as a caregiver, as a parent, you know, taking him up and down Seattle to every therapy possible, quite frankly, you know, it took me years, not, you know, days or months or weeks. And then I realized that nothing had happened to me, but something had happened to my son and I needed to be there for my son. And that is the experience I talk a lot about, but there's experiences like that every day, right? Some colleague of mine comes with some, you know, parent of theirs who needs care, right? That sort of, you know, I learned from it. Or at least, let me put it this way. I am more attuned to learning from other people's experiences today than I was in the beginning of my career. And I think that happens to all of us, right? Which is, life's experiences, they accrue that ability to build a deeper empathy for other people. And that also helps you be a better manager, a better co-worker, a better innovator. Yeah, thanks for sharing. Do you think there is a contradiction between empathy and execution? I don't, right? I think that at the end of the day, to me, you have to take accountability, right? So this is one of the things that in business, like in life too, right? You have to be accountable for making real progress. One of the things I think about, why do businesses exist? Businesses exist, at least, I like this Colin Mayer definition that you have to create profitable solution to challenges of people and planet. Because that's at least a good way to allocate the global resources that are available, right? The profit motive is a good motive because it means you're competing and allocating resources in the most efficient ways and face competition. And so therefore, you have to have great execution, you have to have great accountability. And so I think of empathy as a necessary condition to create great solutions that are profitable and that are competitive solutions that are winning in the marketplace as opposed to somehow this being a trade-off. When you look at your skill set and your personality, what do you think it is that makes you so effective as a leader? I mean, first of all, right, I don't think of this as, I don't know, I have causality here well understood because quite frankly, it's so much easier for others to opine on this than or rather, it's just really for others to judge and assign causality there. But the way at least I come at this is I don't start with what am I good at? I am very keenly shaped by what am I not good at? In other words, I'm always looking what can I learn from someone else? If there's one attribute I have, I don't start each day by thinking, oh, all the stuff I know and I'm good at. I'm like, wow, what am I weak at? Whom do I talk to? Whom do I meet? How do I really shape the colleagues around me who have better skills than me on many fronts? That's what I'm wired. Maybe that helps but I don't know whether that's the causality but I don't start each day with saying, wow, I'm so good at this so therefore, I'm going to go do this. No, I come at the exact opposite. Is this something you learned from Bill Gates because he said the same thing, right? He's really a learner too, right? It's interesting. I don't know. I mean, it's a good point. Both Bill and Steve, there is a sense at Microsoft, I think that that's an interesting thing. We're going to be 50 years next year. There is what Andy Grove would talk, the paranoid survivor, what have you and I don't come at it with paranoia, right? I mean, I don't like paranoia. I like this. That's why I go back to my own words for this. That's why the growth mindset of confronting your own fixed mindset, having confidence and wow, what an unbelievable world we live in that every customer can teach me, every partner can teach me, every colleague can teach me, like what more can I ask for in life? So it's not paranoia. It's not like, oh, wow, we have to go in every day that if I don't learn something, I'll fail. I'm more about like, what do I learn so that I can innovate? Maybe that's how I come at it. And that's right. Bill and Steve in their own unique way had that mindset and so I've grown up around it. And how do you install that kind of, I mean, it is humbleness in a way, right? How do you install that in an organization? You know, at the end of the day, you know, humbleness is an interesting word, right? I always say that you need confidence and humility and not hubris, right? Because there is, sometimes confidence with humility can allow you to really make great progress, but confidence that translates into hubris can bring, you know, it's the downfall of, you know, civilizations, empires and individuals, right? And from ancient Greece to modern Silicon Valley. And so that's why I think you have to sort of really get that calibration that you've got to have some confidence in your own capability. You said in the podcast with our common friend, Adam Grant, that your father, he had a list of people he met and a list of ideas generated. Have you got a list of people you want to meet? Yeah. He had this, you know, he had this note in his diaries were full of that schema, which is people met, ideas generated and tasks completed, which I love, which is a beautiful way each day to keep a count of and absolutely. So that's sort of like, I took that to heart and that's essentially how, that's my framework for life as well. Another thing that makes you stand out is, you know, there is a saying, most people ignore most poetry because most poetry ignores most people. That's clearly, clearly not the case for you. Tell me about your love for poetry. I love poetry, you know, the biggest, in an interesting way, I got into poetry very late. My mom was a professor of Sanskrit drama and so she really instilled in me or at least tried to instill in me the love for, you know, poetry and in her case, you know, Sanskrit literature and poetry and what have you. But I think of it as compression. It's the best. Like when you think about code, it's as I coded more is when I sort of felt like, wow, poetry is basically natural language compression and is able to describe, you know, it's a model of the world in the most succinct form and so there's, and I got into Urdu poetry in a big way in my mid-30s and so I grew up in Hyderabad where obviously Urdu poetry was in the air and now, of course, I love it but even, you know, the American poets, the English romantics, Germans, they're fascinating. So I'm at least, I'm not, I wouldn't say I know much poetry but at least I'm fascinated by the ability of the human mind to compress thought whether it's code or poetry. Well, that's fantastic. Last question, Satya, we have tens of thousands of young people listening to this. What is your best advice to young people? I'd say the best, you know, advice for anyone starting out in, oh, you know, it's sort of advice I got which I paraphrase as never wait for your next job to do your best work, right? Which is, one of the things is any job you get, like I don't remember ever at Microsoft feeling like, oh, I have to get a promotion in order to feel more satisfied or more fulfilled because I somehow felt I had gotten the lottery and I was in the best job I could ever be in. And I'm not saying you shouldn't have ambition, you shouldn't strive for your next promotion, you shouldn't advocate for yourself or have others. You absolutely should do all that. But at the same time, really my advice would be also to take the job you have at hand and do a wonderful, you know, go at it with all of you, the vigor and all of the energy and also define it as broadly as possible, right? I mean, that is perhaps one of the things when I look back at it. I never defined my job narrowly. And that, I think, was both very satisfying in the moment and it helped, I think, land me the next job. And so that is my, perhaps, the one advice I would leave people with. Well, I cannot think of anybody who is doing a better job than you. So, big thanks for being on the show. Good luck with everything and, you know, all the best. Thank you so much, Nikolaj. It's such a pleasure.