Kevin Scott: Microsoft CTO | Lex Fridman Podcast #30
the following is a conversation with Kevin Scott the CTO of Microsoft before that he was the senior vice president of engineering and operations at LinkedIn and before that he oversaw mobile ads engineering at Google he also has a podcast called behind the tech with Kevin Scott which I'm a fan of this was a fun and wide-ranging conversation that covered many aspects of computing it happened over a month ago before the announcement that Microsoft's investment open the eye that a few people have asked me about I'm sure there'll be one or two people in the future they'll talk with me about the impact of that investment this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars in iTunes supported on a patreon or simply connect with me on Twitter at lex friedman spelled fri d-m am and I'd like to give a special thank you to Tom and a lot the big housing for their support of the podcast on patreon thanks Tom and alon the-- hope I didn't mess up your last name too bad your support means a lot and inspires me to keep the series going and now here's my conversation with Kevin Scott you described yourself as a kid in a candy store at Microsoft because of all the interesting projects that are going on can you uh try to do the impossible task and give a brief whirlwind view of all the spaces that Microsoft is working in it was the research and product if you include research it becomes even even more difficult so so like I think broadly speaking Microsoft's product portfolio includes everything from a big cloud business like a big set of SAS services we have you know sort of the original or like some of what are among the original productivity software products that everybody uses we have an operating system business we have a hardware this where we make everything from computer mice and headphones high-end high-end personal computers and laptops we have a fairly broad ranging research group where like we have people doing everything from economics research so like this is really a really smart young economist Glenn Weil who like my group works with a lot who's doing this research on these things called radical markets like he's written an entire entire technical book about about this whole notion of a radical market so like the research group sort of spans from that human-computer interaction to artificial intelligence and we have a we have github we have LinkedIn we have a search advertising and news business and and like probably a bunch of stuff that I'm embarrassingly not recounting and in this gaming to Xbox and so on yeah gaming for sure like I was I was having a super fun conversation this morning with with Phil Spencer so when I was in college there was this game that Lucas arts made called day of the tentacle that my friends and I played forever and like we're you know doing some interest in collaboration now with the folks who made day of the tentacle and I was like completely nerding out with Tim Schafer like the guy who wrote a day of the tentacle this morning just a complete fanboy which you know sort of it like happens a lot like you know Microsoft has been doing so much stuff it's such breadth for such a long period of time that you know like being CTO like most of the time my job is very very serious and sometimes like I get to I get caught up and like how amazing it is to be able to have the conversations that I have with the people I get to have them with you had to reach back into the sentimental and what's the the wreck of radical markets and they and they had economics so there the idea with radical markets is like can you come up with new market-based mechanisms - you know I think we have this we're having this debate right now like does capitalism work like free markets work can the incentive structures that are built into these systems produce outcomes that are creating sort of equitably distributed benefits for every member of society you know and I think it's a reasonable reasonable set of questions to be asking and so what Glenn and so like you know one motor thought they're like if you have doubts that the that the markets are actually working you can sort of like tip towards like okay let's let's become more socialist and you know like have central planning and you know governments or some other central organization it's like making a bunch of decisions about how you know sort of work gets done and you know like where the you know where the investments and where the outputs of those investments get distributed Glenn's notion is like lean more into like the market-based mechanism so like for instance you know this is one of the more radical ideas like suppose that you had a radical pricing mechanism for assets like real estate where you were you could be bid out of your position and in in your home you know for instance so like if somebody came along and said you know like I've I can find higher economic utility for this piece of real estate that you're running your your business and like then like you either have to you know sort of bid to sort of stay or like the thing that's got the higher economic utility you know sort of takes over the asset and which would make it very difficult to have the same sort of rent seeking behaviors that you've got right now because like if you did speculative bidding like you would you very quickly like lose a whole lot of money and so like the prices of the assets would be sort of like very closely index to like the value that they can produce and like because like you'd have this sort of real-time mechanism that would force you to sort of mark the value of the asset to the market then it could be taxed appropriately like you couldn't sort of sit on this thing and say oh like this house is only worth ten thousand bucks when like everything around it is worth ten million let's finish so it's an incentive structure that where the prices matched the value much better yeah so the Anglin does a much much better job than I do at selling and I probably picked the world's worst example you know and and in but like in its it's intentionally provocative you know so like this whole notion like I you know like I I'm not sure whether I like this notion that like we could have a set of market mechanisms where I could get bit out of faith that was my property you know but but you know like if you're thinking about something like Elizabeth Warren's wealth tax for instance like you would have I mean you'd be really interesting in like how you would actually set the the price on the assets and like you might have to have a mechanism like that if you put a tax like that in place it's really interesting that that kind of research at least tangentially is touching Microsoft Research yeah the years really thinking broadly that maybe you can speak to this connects to AI so we have a candidate Andrew yang who kind of talks about artificial intelligence and the concern that people have about art you know automations impact on society and arguably Microsoft is at the cutting edge of innovation in all these kinds of ways and so it's pushing AI forward how do you think about combining all our conversations together here with radical markets and socialism and innovation in a item that Microsoft is doing and then Andrew Yang's worried that that that will that will result in job loss for the low and so on how do you think about that I think it's sort of one of the most important shins and Technology like maybe even in society right now about how is AI going to develop over the course of the next several decades and like what's it going to be used for and like what what benefits will it produce and what negative impacts will it produce and you know how who gets to steer this whole thing you know I'll say it at the highest level one of the real joys of getting to do what I do at Microsoft is Microsoft has this heritage as a platform company and so you know like Bill Bill's has this thing that he said a you know a bunch of years ago where you know the the measure of a successful platform is that it produces far more economic value for the people who build on top of the platform than is creative for the the platform owner or builder and I think we have to think about AI that way like satellite form yeah it has to like it has to be a platform that other people can use to build businesses to fulfill their creative objectives to be entrepreneurs to solve problems that they have in their work and in their lives it can't be a thing where there are a handful of companies sitting in a very small handful of city cities geographically who are making all the decisions about what goes into the AIA and and and like and then on top of like all this infrastructure then build all of the commercially valuable uses for it so like I think like that's bad from a you know sort of you know economics and sort of equitable distribution of value perspective like you know sort of back to this whole notion of you know like do the markets work but I think it's also bad from an innovation perspective because like I have infinite amounts of faith in human beings that if you you know give folks powerful tools they will go do interesting things and it's more than just a few tens of thousands of people with the interesting tools it should be millions of people with the tools so sort of like you know you think about the the steam engine and the late 18th century like it was you know maybe the first large-scale substitute for human labor that we've built like a machine and you know in the beginning when these things are getting deployed the folks who got most of the value from the steam engines were the folks who had capital so they could afford to build them and like they built factories around them in businesses and the experts who knew how to build and maintain them but access to that technology democratized over time like now like like an engine is not a it's not like a differentiated thing like there isn't one engine company that builds all the engines and all of the things that use engines are made by this company and like they get all the economics from all of that like never like fully democratize like they're probably you know we're sitting here in this room and like even though they don't that they're probably things you know like the the MEMS gyroscope that are in both of our float like there's like little engines you know sort of everywhere they they're just a component and how we build the modern world like AI DS to get there yeah so that's a really powerful way to think if we think of AI is a platform versus a tool that Microsoft owns as a platform that enables creation yeah on top of it that's a way to democratize it that's really absolutely interesting actually and Microsoft in its history has been positioned well to do that and the you know the tie back to the to this radical markets thing like the so my team has been working with Glenn on this and Jaron Lanier actually did just so Jaron is the like the sort of father of virtual reality like he's one of the most interesting human beings on the planet like a sweet sweet guy and so Jaron and Glen and folks in my team have been working on this notion of data as labor or like they call it data dignity as well and so the the idea is that if you you know again going back to this you know sort of industrial analogy if you think about data is the raw material that is consumed by the machine of AI in order to do useful things then like we're not doing a really great job right now and having transparent marketplaces for valuing those data contributions so like and we all make them like explicitly like you go to LinkedIn you sort of set up your profile on LinkedIn like that's an explicit contribution like you know exactly the information that you're putting into the system and like you put it there because you have some nominal notion of like what value you're gonna get in return but it's like only nominal like you don't know exactly what value you're getting in return like service is free you know like it's low amount of like procedure and then you've got all this indirect contribution that you're making just by virtue of interacting with all of the technology that's in your daily life and so like what Glen and Jaron and and this data Dignity team are trying to do is like can we figure out a set of mechanisms that let us value those data contributions so that you could create an economy and like a set of controls and incentives that would allow people to like maybe even in the limit like earn part of their living through the data that they're creating and like you can sort of see it in explicit ways they're these companies like scale AI and like they're a whole bunch of them in in China right now that are basically data labeling companies so like you you're doing supervised machine learning you need you need lots and lots of label training data and like those people are getting competent like who worked for those companies are getting compensated for their data contributions into the system and so that's easier to put a number on their contribution because they're explicitly labeling they're correct but you're saying that we're all contributing data in all kinds of ways and it's fascinating to start to explicitly try to put a number on it do you think that's you that's possible I don't know it's hard it really is because you know we don't have as much transparency as is I think we need in like how the data is getting used and it's you know super complicated like you know we we you know I think it's technologists sort of appreciate like some of the subtlety there it's like you know the data the data gets created and then it gets you know it's not valuable like the the data exhaust that you give off or the you know the explicit data that I am putting into the system isn't value valuable it's super valuable atomically like it's only valuable when you sort of aggregate it together and you know sort of large numbers it's true even for these like folks who are getting compensated for like labeling things like for supervised machine learning now like you need lots of labels to train a you know a model that performs well and so you know I think that's one of the challenges it's like how do you you know how do you sort of figure out like because this data is getting combined in so many ways like through these combinations like how the value is flowing yeah that's that's that's tough yeah and it's fascinating that you're thinking about this and I wish I wasn't even going to this conversation expecting the breadth of research really that Microsoft broadly is thinking about you are thinking about it Microsoft so if we go back to 89 when Microsoft released office or 1990 when they at least windows 3.0 house.the in your view I know you weren't there the entire you know there was history but how is the company changed in the 30 years since as you look at it now the good thing is it's started off as a platform company like it's still a platform company like the parts of the business that are like thriving and most successful or those that are building platforms like the mission of the company now is the missions change it's like changing a very interesting way so you know back in 89 90 like they were still on the original mission which was like put a PC on every desk and in every home like in it was basically about democratizing access to this new personal computing technology which when Bill started the company integrated circuit micro processors were a brand-new thing and like people were building you know homebrew computers you know from kits like the way people build ham radios right now yeah and I think this is sort of the interesting thing for folks who build platforms in general Bill saw the opportunity there and what personal computers could do and it was like it was sort of a reach like you just sort of imagined like where things were you know when they started the company versus where things are now like in success when you've democratized a platform it just sort of vanishes into the platform you don't pay attention to it anymore like operating systems aren't a thing anymore like they're super important like completely critical and like you know when you see one you know fail like you you just you sort of understand but like you know it's not a thing where you're you're not like waiting for you know the next operating system thing in the same way that you were in 1995 right that's like in 1995 like you know we have Rolling Stones on the stage with the windows 95 rollout like it was like the biggest thing in the world everybody was lined up for it the way that people used to line up for iPhone but like you know eventually and like this isn't necessarily a bad thing like it just sort of you know it the success is that it's sort of it becomes ubiquitous it's like everywhere and like human beings when their technology becomes ubiquitous they just sort of start taking it for granted so the mission now that Satya Ari articulated five plus years ago now when he took over as CEO of the company a mission is to empower every individual and every organization in the world to be more successful and so you know again like that's a platform mission and like the way that we do it now is is different it's like we have a hyper scale cloud that cloud or building our applications on top of like we have a bunch of AI infrastructure that people are building their AI applications on top of we have you know we have a productivity suite of software like Microsoft Dynamics which you know some people might not think is the sexiest thing in the world but it's like helping people figure out how to automate all of their business processes and workflows and you know like help those businesses using it to like grow and be more so so it's it's a much broader vision in a way now than it was back then like it was sort of very particular thing and like now like we live in this world where technology is so powerful and it's like such a basic fact of life that it you know that it it both exist and is going to get better and better over time or at least more and more powerful over time so like you know what you have to do is a platform player is just much bigger right there's so many directions in which you can transform you didn't mention mixed reality yeah you know that's yep that's that's probably early days or depends how you think of it but if we think on a scale of centuries just the early days of mixed reality oh for sure and so yeah with hololens the Microsoft is doing some really interesting work there do you touch that part of the effort what's the thinking do you think of mixed reality as a platform to know sure when we look at what the platform's of the future could be so like fairly obvious that like AI is one like you don't have to I mean like that's you know you sort of say it like someone and you know like they get it but like we also think of the like mixed reality and quantum is like these two interesting you know potential computing yeah okay so let's get crazy then so so you're talking about some futuristic things here well the mixed reality Microsoft is really it's not even feature a stick is here it is incredible stuff and it in look and it's heaven and it's having impact right now like one of the one of the more interesting things this happened with NYX reality over the past couple of years that I didn't clearly see is that it's become the computing device for for folks who for doing their work who haven't used any computing device at all to do their work before so technicians and service folks and people who are doing like machine maintenance some factory floors so like they you know but because they're mobile and like they're out in the world and they're working with their hands and you know sort of servicing these like very complicated things they're they don't use their mobile phone and like they don't carry a laptop with them and you know they're not tethered to a desk and so mixed reality like where it's getting traction right now where hololens is selling a lot of a lot of units is for these sorts of applications for these workers and it's become like I mean like the people love it they're like oh my god like this is like for them like the same sort of productivity boost that you know like an office worker had when they got their first personal computer yeah but you did mention it's really obvious AI as a platform but can we dig into it a little bit red how does a I begin to infuse some of the products in Microsoft so currently providing training of for example neural networks in the cloud yeah we're providing put pre train models or just even providing computing resources whatever different inference that you want to do using you on that works yep well how do you think of AI infusing the as a platform that Microsoft can provide yeah I mean I think it's it's super Android it's like everywhere and like we we run these we run these review meetings now where it's be and satya and like members of sathyas leadership team and like a cross-functional group of folks across the entire company who are working on like either AI infrastructure or like have some substantial part of their of their product work using AI in some significant way now the important thing to understand is like when you think about like how the AI is gonna manifest in like an experience for something that's gonna make it better like I think you don't want the a eyeness to be the first-order thing it's like whatever the product is and like the thing that is trying to help you do like the AI just sort of makes it better and it you know this is a gross exaggeration but like i yet people get super excited about like where the AI is showing up in products and i'm like do you get that excited about like where you using a hash table that code like it's just another just the tool it's a very interesting programming tool but it's sort of a like it's an engineering tool and so like it shows up everywhere so like we've got dozens and dozens of features now in office that are powered by like fairly sophisticated machine learning our search engine wouldn't work at all if you took the machine learning out of it the like increasingly you know things like content moderation on our Xbox and X cloud platform you know when you mean moderation to be like the recommenced it's like showing what you want to look at next no no it's like anti-bullying so that's that so you use your social network stuff they yeah deal with yeah correct but it's like really it's targeted it's targeted towards a gaming audience so it's like a very particular type of thing where you know the the line between playful banter and like legitimate bullying is like a subtle one and like you have to like it's sort of tough like I have I'd love to if we could dig into it because you're also you let the engineering efforts to LinkedIn yep and if we look at if we look at LinkedIn as a social network yeah and if we look at the Xbox gaming is the social components the very different kinds of I imagine communication going on on the two platforms yeah right and the line in terms of bullying and so on is different on the GUP platforms so how do you I mean in such a fascinating philosophical discussion of where that line is I don't think anyone knows the right answer Twitter folks are under fire now Jack a Twitter for trying to find that line nobody knows what that line is but how do you try to find the line for you know trying to prevent abusive behavior and at the same time let people be playful and joke around and that kind of thing I think in a certain way like even if you have what I would call vertical social networks it gets to be a little bit easier so like if you have a clear notion of like what your social network should be used for or like what you are designing a community around then you don't have as many dimensions to your sort of content safety problem as you know as you do in a general purpose I mean so like on on LinkedIn like the whole social network is about connecting people with opportunity whether it's helping them find a job or to you know sort of find mentors or to you know sort of help them like find their next sales leave or to just sort of allow them to broadcast their their you know sort of professional identity to their their network of peers and collaborators and you know sort of professional community like that is I mean in like in some ways like that's very very broad but in other ways it's sort of you know it's narrow and so like you can build a eyes like machine learning systems that are you know capable with those boundaries of making better automated decisions about like what is you know sort of inappropriate and offensive comments or dangerous comments or illegal content when you have some constraints you know same thing with the same thing with like the gaming gaming social network sufferance it's like it's about playing games not having fun and like the thing that you don't want to have happen on the platform it's why bullying is such an important thing like bullying is not fun and also you want to do everything in your power to encourage that not to happen and yeah I but I think it's it's sort of a tough problem in general it's one where I think you know eventually we're gonna have to have some sort of clarification from our policymakers about what it is that we should be doing like where the lines are because it's tough like you don't like in democracy right like you don't want you want some sort of democratic involvement like people should have a say in like where where the lines lines are drawn like you don't want a bunch of people making like unilateral decisions and like we are in a we're in a state right now for some of these platforms where you actually do have to make unilateral decisions where the policy-making isn't gonna happen fast enough in order to like prevent very bad things from happening but like we need the policy-making side of that to catch up I think is as quickly as possible because you want that whole process to be a democratic thing not a you know not not some sort of weird thing where you've got a non representative group of people making decisions that have you know like national and global impact as fascinating because the digital space is different than the physical space and which nations and governments were established and so what policy looks like globally what bullying looks like globally what healthy communication looks like global is there's open question and we're offering and freaking it out yeah I mean with you know sort of fake news for instance and deep fakes and fake news generated by humans yeah so even we can talk about defects like I think that is another like you know sort of very interesting level of complexity but like if you think about just the written word right like we have you know we invented papyrus what's three thousand years ago where we you know you could sort of put put word on on paper and then five hundred years ago like we we get the printing press like where the word gets a little bit more ubiquitous and then like you really really didn't get ubiquitous printed word until the end of the nineteenth century when the offset press was invented and then you know just sort of explodes and like you know the cross-product of that and the industrial revolutions need for educated citizens resulted in like this rapid expansion of literacy and the rapid expansion of the word but like we had three thousand years up to that point to figure out like how to you know like what's what's journalism what's editorial integrity like what's you know what's scientific peer review and so like he built all of this mechanism to like try to filter through all of the noise that the technology made possible to like you know sort of getting to something that society could cope with and like if you think about just the piece the PC didn't exist fifty years ago and so in like this span of you know like half a century like we've gone from no digital you know no ubiquitous digital technology to like having a device that sits in your pocket where you can sort of say whatever is on your mind to like what would it Mary Heaven or mary meeker just released her new like slide deck last week you know we've got 50 percent penetration of the the internet to the global population like they're like three and a half billion people who are connected now it's it's like it's crazy crazy croelick inconceivable like how all of this happens so you know it's not surprising that we haven't figured out what to do yet but like I gotta like we got a really like lean into this set of problems because like we basically have three millennia worth of work to do about how to deal with all of this and like probably what yeah amounts to the next decade worth of time so since were on the topic of tough tough you know tough challenging problems let's look at more on the tooling side in AI that Microsoft is looking at space recognition software so there's there's a lot of powerful positive use cases yeah for face recognition but there's some negative ones and we're seeing those in different governments in the world so how do you how does Microsoft think about the use of face recognition software as a platform in governments and companies yeah how do we strike an ethical balance here yeah I think we've articulated a clear point of view so Brad Smith wrote a blog post last fall I believe this sort of like outline like very specifically what you know whatever what our point of view is there and you know I think we believe that there are certain uses to which face recognition should not be put and we believe again that there's a need for regulation there like the the government should like really come in and say that you know this is this is where the lines are and like we very much wanted to like figuring out where the lines are should be a democratic process but in the short term like we've drawn some lines where you know we push back against uses of face recognition technology you know like this city of San Francisco for instance I think is completely outlawed any government agency from using face recognition tech and like that may prove to be a little bit overly broad but for like certain law enforcement things like you you really III would personally rather be overly sort of cautious in terms of restricting use of it until like we have you know to find a reasonable democratically determined regulatory framework for like where we we could and should use it and you know the the other thing there is like we've got a bunch of research that we're doing and a bunch of progress that we've made on on bias there and like there all sorts of like weird biases that these models can have like all the way from like the most noteworthy one where you know you may have underrepresented minorities who are like underrepresented in the training data and then you start learning like strange things but like they're they're even you know other weird things like we've I think we've seen in the public research like models can learn strange things like all doctors or men for instance just yeah i mean so like it really is a thing where it's very important for everybody who is working on these things before they push publish they launch the experiment they you know push the code you know online or they even publish the paper that they are at least starting to think about what some of the potential negative consequences are some of this stuff i mean this is where you know like the deep fake stuff I find very worrisome just because there gonna be some very good beneficial uses of like Gann generated imagery and I and funny enough like one of the places where it's actually useful is we're using the technology right now to generate synthetic synthetic visual data for training some of the face recognition models to get rid of the bias right so like that's one like super good use of the tech but like you know it's getting good enough now where you know it's gonna sort of challenge normal human beings ability to like now you're just sort of say like it's it's very expensive for someone to fabricate a photorealistic fake video and like ganzar gonna make it fantastically cheap to fabricate a photorealistic fake video and so like what you assume you can sort of trust as true versus like be skeptical about is about to change yeah and like we're not ready for it I don't think the nature of truth right that's uh it's also exciting because I think both you and I probably would agree that the way to solve to take on that challenge is with technology yeah right there's probably going to be ideas of ways to verify which which kind of video is legitimate which kind of is not so to me that's an exciting possibility most most likely for just the comedic genius that the internet usually creates with these kinds of videos yeah and hopefully will not result in any serious harm yeah and it could be you know like I think we will have technology too that may be able to detect whether or not something's fake a real although yeah the the fakes are pretty convincing even like when you subject them to machine scrutiny but you know that we we also have these increasingly interesting social networks you know that are under fire right now for some of the bad things that they do like one of the things you could choose to do with a social network is like you could you could use crypto and the networks to like have content signed where you could have a like full chain of custody that accompanied every piece of content so like when you're viewing something and like you want to ask yourself like how you know how much can I trust this like you can click something and like have a verified chain of custody that shows like oh this is coming from you know from this source and it's like sign I like someone whose identity I trust yeah yeah I think having that you know having that Chain of Custody like being able to like say oh here's this video like it may or may not have been produced using some of this deep fake technology but if you've got a verified Chain of Custody where you can sort of trace it all the way back to an identity and you can decide whether or not like I trust this identity like oh no this is really from the White House or like this is really from the you know the office of this particular presidential candidate or it's really from you know Jeff Weiner CEO of of LinkedIn or Satya Nadella CEO Microsoft like that might that might be like one way that you can solve some of the problems and so like that's not the super high tech like we've had all of this technology forever and back but I think you're right like it has to it has to be some sort of technological thing because the the underlying tech that is used to create this isn't not going to do anything but get better over time and the genie is sort of out of the bottle there's no stuffing it back in and there's a social component which i think is really healthy for a democracy where people be skeptical about the thing they watch yeah in general so you know which is good skepticism in general is good and it's good content so deep fakes in that sense of creating global skepticism about can they trust what they read it encourages further research I come from the Soviet Union where basically nobody trusted the media because you knew it was propaganda and that encouraged that kind of skepticism encouraged further research about ideas yeah posters just trusting any one source look I think it's one of the reasons why the the you know the scientific method and our apparatus of modern science is so good like because you don't have to trust anything like you like the whole notion of you know like modern science beyond the fact that you know this is a hypothesis and this is an experiment to test the hypothesis and you know like this is a peer review process for scrutinizing published results but like stuffs also supposed to be reproducible so like you know it's been better by this process but like you also are expected to publish enough detail where you know if you are sufficiently skeptical of the thing you can go try to like reproduce it yourself and like I I don't know what it is like I think a lot of Engineers are like this where like you know sort of this like your brain is sort of wired for for scepticism like you don't just first order trust everything that you see an encounter and like you're sort of curious to understand you know the next thing but like I think it's an entirely healthy healthy thing and like we need a little bit more of that right now so I'm not a large business owner so I'm just I'm just a huge fan of many of Microsoft products I mean I still actually in terms of I generate a lot of graphics and images and I still use PowerPoint to do that it beats illustrator for me even professional a sort of is this fascinating so I wonder what is the future of let's say windows and office look like is do you see it I mean I remember looking forward to XP wasn't exciting yep when XP was released just like you said I don't remember when 95 was released but xp for me it was a big celebration and and 110 came out I was like okay what's nice it's a nice improvement but yeah so what do you see is the future of these products and you know I think there's a bunch of exciting I mean though in the office front there's going to be this like increasing productivity winds that are coming out of some of these AI powered features that are coming like the products are sort of get smarter and smarter in like a very subtle way like there's not gonna be this Big Bang moment where you know like Clippy is gonna reimagined it's gonna wait a minute okay well have that wait wait wait Clippy coming back in but quite seriously so injection of AI there's not much or at least I'm not familiar sort of assistive type of stuff going on inside the office products in like a clippie style a assistant personal assistant do you think that there's a possibility of the future alright so I think they're a bunch of like very small ways in which like machine learning power and assistive things are in the product right now so there are there a bunch of interesting things like the auto response stuffs getting better and better and it's like getting to the point where you know it can auto respond with like okay let you know this person is clearly trying to schedule a meeting so it looks at your calendar and it automatically electrons to fines like a time in a space that's mutually interesting like we we have this notion of Microsoft search where it's like not just web search but it's like search across like all of your information that's sitting inside of like your office 365 tenant and like you know potentially in other products and like we have this thing called the Microsoft graph that is basically a API federated at you know sort of like gets you hooked up across the entire breadth of like all of the you know like what were information silos before they got woven together with the graph like that is like getting increasing with increasing effectiveness sort of plumbed into the into some of these auto-response things where you're gonna be able to see the system like automatically retrieve information for you like if you know like I frequently send out you know emails to folks were like I can't find a paper or a document or whatnot there's no reason why the system won't be able to do that for you and like I think the the its building towards like having things that look more like like a fully integrated you know assistant but like you'll have a bunch of steps that you will see before you like it will not be this like Big Bang thing where like Clippy comes back and you've got this like you know manifestation of you know like a fully fully powered assistant so I think that's that's definitely coming in like all of the you know collaboration co-authoring stuff's getting better you know it's like really interested like if you look at how we use like the office product portfolio at Microsoft like more and more of it is happening inside of like teams as a canvas and like it's this thing where you know you've got collaboration is like at the center of the product and like we we built some like really cool stuff that's some of which is about to be open source that are sort of framework level things for doing for doing co-authoring so in is there a cloud component to that so on the web or is it I forgive me if I don't already know this but with office 365 we still the collaboration would do if you're doing word which still send the file around no advice yeah this is it we're already a little bit better than that and like you know so the fact that you're unaware of it means we've got a better job to do feel like helping you discover discover this stuff but yeah I mean it's already like got a huge huge clock but and like part of you know part of this framework stuff I think we're calling it like I like we've been working on it for a couple years so like I know the the internal code name for it but I think when we launched it a bill is called a fluid framework and but like what fluid lets you do is like you can go into a conversation that you're having in teams and like reference like part of a spreadsheet that you're working on where somebody's like sitting in the Excel canvas like working on the spreadsheet with a you know chart or whatnot and like you can sort of embed like part of the spreadsheet in the team's conversation where like you can dynamically update it and like all of the changes that you're making to the to this object are like you know coordinate and everything is sort of updating in real time so you can be in whatever canvas is most convenient for you to get your work done so I out of my own sort of curiosity is engineer I know what it's like to sort of lead a team of 10 50 Engineers Microsoft has I don't know what the numbers are maybe fifty maybe sixty thousand engineers with a lot more genius I don't know exactly what the number is it's a lot it's it's tens of thousands sites this is more than ten or fifteen what I mean you've uh you've led different sizes mostly large size of Engineers what does it take to lead such a large group into a continued innovation continue being highly productive and yet develop all kinds of new ideas and yet maintain like what does it take to lead such a large group of brilliant people I think the thing that you learn as you manage larger and larger scale is that there are three things that are like very very important for big engineering teams like one is like having some sort of forethought about what it is that you're gonna be building over large periods of time like not exactly like you don't need to know that like you know I'm putting all my chips on this one product and like this is gonna be the thing but like it's useful to know like what sort of capabilities you think you're going to need to have to build the products of the future and then like invest in that infrastructure like whether and I like I'm not just talking about storage systems or cloud api's it's also like what does your development process look like what tools do you want like what culture do you want to build around like how you're you know sort of collaborating together to like make complicated technical things and so like having an opinion and investing in that is like it just gets more and more important and like the sooner you can get a concrete set of opinions like the better you're going to be like you can wing it for a while small scales like you know when you start a company like you don't have to be like super specific about it but like the biggest miseries that I've ever seen as an engineering leader are in places where you didn't have a clear enough opinion about those things soon enough and then you just sort of go create a bunch of technical debt and like culture debt that is excruciating ly painful to to clean up so like that's one bundle of things like the other the other you know another bundle of things is like it's just really really important to like have a clear mission that's not just some cute crap you say because like you think you should have a mission but like something that clarifies for people like where it is that you're headed together like I know it's like probably like a little bit too popular right now but you've all her re book sapiens one of the central ideas and in his book is that like storytelling is like the quintessential thing for coordinating the activities of large groups of people like once you get past Dunbar's number and like I've really really seen that just managing engineering teams like you you can you can just brute force things when you're less than 120 hundred fifty folks where you can sort of know and trust and understand what the dynamics are between all the people but like past that like things just sort of start to catastrophic ly fail if you don't have some sort of set of shared goals that you're marching towards and so like even though it sounds touchy-feely and you know like a bunch of technical people will sort of balk at the idea that like you need to like have a clear like the missions like very very very important you've always write write stories that's how our society that's the fabric that connects us all of us is these powerful stories and that works for companies - and it works for everything like it mean even down to like you know you sort of really think about like a currency for instance is a story a constitution is a story our laws or story I mean like we believe very very very strongly in them and thank God we do but like they are there they're just abstract things like they're just words it's like we don't believe in them they're nothing and in some sense those stories are platforms and the kinds some of which Microsoft is creating right you have platforms on which we define the future so last question what do you think if philosophical maybe bigger than you know Microsoft what do you think the next 20 30 plus years looks like for computing for technology for devices do you have crazy ideas about the future of the world yeah look I think we you know we're entering this time where we've got we have technology that is progressing at the fastest rate that it ever has and you've got you get some really big social problems like society scale problems that we have to we have to tackle and so you know I think we're gonna rise to the challenge and like figure out how to intersect like all of the power of this technology with all of the big challenges that are facing us whether it's you know global warming whether it's like the biggest remainder of the population boom is in Africa for the next 50 years or so and like global warming is gonna make it increasingly difficult to feed global population in particular like in this place where you're gonna have like the biggest population boom I think we you know like AI is gonna like if we push it in the right direction like you can do like incredible things to empower all of us to achieve our full potential and to you know like live better lives but like that also means focus on like some super important things like how can you apply it to health care to make sure that you know like air quality and cost oh and in sort of ubiquity of health coverage is is better and better over time like that's more and more important every day is like in the in the United States and like the rest of the industrialized were also in Europe China Japan Korea like you've got this population bubble of like aging working you know working aged folks who are you know at some point over the next 20-30 years they're gonna be largely retired and like you you're gonna have more retired people than working age people and then like you've got you know sort of natural questions about who's gonna take care of all the old folks and who's gonna do all the work and the the answers to like all of these sorts of questions like where you're sort of running into you know like constraints of the you know the the world and of society has always been like what tech is gonna like help us get around this you know like when I was when I was a kid in the seventies and eighties like we talked all the time about like oh like population boom population boom like we're gonna like we're not gonna be able to like feed the planet and like we were like right in the middle of the Green Revolution we're like this this massive technology driven increase in crop productivity like worldwide and like some of that was like taking some of the things that we knew in the West and like getting them distributed to the you know to the to the developing world and like part of it were things like you know just smarter biology like helping us increase and like we don't talk about like yep overpopulation anymore because like we can more or less we sort of figured out how to feed the world like that's a that's a technology story and so like I'm super super hopeful about the future and in the ways where we will be able to apply technology to solve some of these super challenging problems like I've I've like one of the things that I I'm trying to spend my time doing right now is trying to get everybody else to be hopeful as well because you know back to the Harare like we we are the stories that we tell like if we you know if we get overly pessimistic right now about like the the potential future of technology like we you know like we may fail to fail to get all the things in place that we need to like have our best possible future and that kind of hopeful optimism I'm glad that you have it because you're leading large groups of engineers that are actually defining that are writing that story that are helping build that future which is super exciting and I agree with everything you said except I do hope cliff he comes back haha we miss him I speak for the people Alan thank you so much for talking to now thank you so much for having me it was pleasure you