We will incorporate this in our own application, so you can fully expect us to, obviously every product of Microsoft will have some of the same AI capabilities to completely transform the product. - To jump right into it, let's talk about artificial inteligence. It's a big topic already
in everybody's mind here. There's already been quite a
bit of speculation given to me that in seven or eight
years this interview will be conducted by some kind
of artificial inteligence, which might make it better that there won't be journalists here, there'll be machines
doing all of the work, which also could be an
improvement for all, I know. You guys obviously are
an investor at OpenAI. You've invested more, there are many reports out
there that you are looking to invest more. I think 10 billion has been thrown around as the number out there. You see, you have an inside
view of the technology. Can you just put in
some broad perspective? We saw the demo, we've all experienced it. We see the sort of the
dramatic impact it has. How do you assess really holistically where the technology is
and isn't what it does, what it doesn't do, and how big a breakthrough
moment we're at? - Yeah, first of all, yeah, I wish I had put Chat GPT through that security line myself. Let me just kind of give you two anecdotes and then try to generalize it. On New Year's Day this year, I just looked in my newsfeed
and I saw this tweet that Andrej Karpathy, who
is, you know, who was the guy at Tesla who you know, did the autopilot, tweeted saying 80% of
the code he writes today is being written by GitHub Copilot. Think about this, right? This is one of the most
elite AI developers who's saying that they're being
that much more productive. It's not that Andrej is
not doing great AI work, it's just that a lot, he's
getting a ton of leverage, and that's perhaps been
the breakthrough product of this generation of AI in the last year. And it's a real product. It's not some research project
somewhere, what have you. I mean, this is some literally changing the productivity curve
for some of the most of, for software engineers, which was considered the
knowledge worker, you know, or rather the most sort of difficult to automate knowledge work, so to speak. And so that's one. Then the next day I was in
India and I saw this demo, which was just completely stunning for me. I saw someone use one of the
Indian vernacular languages, talking to a bot that Microsoft Research, along with our partners from
the Ministry of Electronics and a program called Bashini which is about trying to basically use AI to get language translation
to be democratized in India. But, so here's essentially someone who is in rural India using one
of their language, you know, of a local language talking
to a bot on WhatsApp, and this bot, basically this person
wanted to have access to some government program. And so he asks about the program, the bot comes back and says, you should go to the
portal and do X, Y, and Z. And he then goes on to say that, look, I don't wanna go to the
portal, just do this for me. And so this is someone in rural India sort of expressing a
pretty complex thought, even if they may not be all literate about how to navigate some
complex set of instructions. And then on the back end of
it, what the team had done was used GPT to essentially train over all of government of India's
documents and made it accessible in every Indian language
and made it automatable. So think about this, I'd
never seen in my life, at least in the 30 years
I've been in tech, ever, a demo where an advance
that happened in say, west coast of the United States, shows up in very real terms for someone in rural India within months. I mean, that is diffusion of technology that I've never seen. I don't think it happened in
the industrial revolution, but maybe this time around in what is sort of the
knowledge worker equivalent of the industrial revolution. It's going to help everybody. So these two things. So the most elite AI developer on one end, and on the other end there
is a rural farmer in India being able to access
government programs through AI. So that's, those two
anecdotes speak to me at least what the power of this thing is. - And from what you
see and where we're at, are we at the early stage of a curve that's rapidly going to
change in the next few years and we're gonna see this kind
of exponential development? - I think that's the key. So what you just said was, what is, why is there so much
more excitement this year than last year is because
of that exponential growth of the power of these models? I'm not claiming by the way
that this is the last innovation in AI or this is the
last model architecture. There's gonna be lots more to come. But if you look at what has
happened between GPT-3 to 3.5 to what comes next, these
are not linear areas, this is not linear progress. - Okay, but the slightly pessimist case, you're an optimist on this
would be, it's exciting. It's rapidly moving. It's a bit terrifying. Knowledge workers, I've
heard it already here at Davos this week already
anxious in some ways about their future jobs and what it means when you see technology
spread on that scale. I have to ask one, are we societally ready for that? And are you really confident
that there's the optimist case that it enhances all of our productivity rather than replaces many of us? - It's a great, it's the right question to ask. I mean, look, I mean the, the first thing I step back and say, when I look at all productivity data, I look at all economic growth data. I sort of look at that and say, God, we need something to help us. It's not like we are as a world growing at inflation adjusted 3, 4%. If we really have the dream
that the 8 billion people plus in the world, their living
standards monotonically should keep improving year over year, what is that input that's
going to cause that? Like what, you know, we need and we have some
tough challenges, right? When you think about energy transition, let's just take that for an example. Essentially, what we are saying, at least the way I as a layman,
layperson understand it, is you gotta take 250 years
of chemistry and compress it into some 25 years so that we can then make it to the other side? If that is the case, computational chemistries
is gonna be super important. And so applications of
AI to that is probably the way we are gonna make it. So I look at it and say, we need something that truly
changes the productivity curve so that we can have real economic growth. And then if you have that, there are all kinds of things
that we can like talk about, which is what does it
mean to displacement, which will be real. After all, there was displacement in the industrial revolution. We went through some lot
of hardship to come up with even an understanding
of how to deal with it. This time around, we have that understanding. So therefore, I would say
first let's not fall into what is the lump of labor fallacy. If you don't fault for that,
then what are all the new jobs? What is the training required? And here's one other
thing I would say, Matt, which if you think about the
way frontline workers today are being enabled with
technology to be able to do what was previously perhaps
considered knowledge work, it's probably the biggest
thing that is underreported, underwritten about then, you
know, we have at Microsoft, a tool called Power Platform, right? So think of it as what is essentially it's
Excel level skills at best even lower, where you can take that tool and create applications, create workflows. In fact, you can use GPT to
essentially prompt a workflow. So that means somebody who's
in the retail frontline, warehouse frontline, healthcare frontline, pick your favorite frontline job where they're not IT specialists, they're not skilled in computer science, they can, in fact, participate
in the digital transformation of their org. If they do that, what
happens next, is better wages because they're now considered to be not just doing frontline work, but are also participating in what was previously knowledge work. So to me, that's an example of, in fact, people participating in the
labor force with better support. - I'm gonna ask you though,
what concerns you when you see, you see seeing things
that we haven't seen yet that aren't public yet? You see what's coming? Tell us a little bit about
what we haven't seen publicly and then, you know, tell us a little bit about where it's going. - Look, I mean, I think the
thing that all the concerns we have around safety, whether it's harmful
content or hallucination or any of these, you
just need to by design, like I mean all software
engineering has to shift left. You have to sort of think about
the model itself being safe. Then you have to, on top of it, have a safety system that is built. And so you have to really take this as a first class engineering
concern and build. And this is not new to just AI, it's true in any other category
of software today as well. - But what do we need to
be doing as a society? And maybe even for the folks in this room, a lot of them are knowledge
workers as individuals to be thinking about and preparing ourself for what's coming. Because as you just sort of even hinted, we haven't wrapped our
heads around social media and what hit us 20 years ago, this is gonna be exponentially faster and probably have a more dramatic impact in the short term on our society. How do we need, what do we need to be
thinking about societally? - You know, the way at least
I come at it is I grew up with sort of the PC revolution starting in the late '80s, and it was just an
empowering moment, right? I mean, even if you
think about my own story, I mean the way I was able to
sort of have this technology, reach me where I was growing up and be able to sort of
get into it and then, you know, and the rest
is, you know, history. So therefore I look at it and say, is it doesn't matter if
you are a knowledge worker or a frontline worker, use these tools to actually
then get more leverage in your job. If Andrej as a software
developer in AI can do that, why can't all of us have access to it. If that farmer in rural
India can use this technology to get their job done, that's the way I think the
best way to prepare for it is to sort of not bet
against this technology and this technology
helping you in your job, in your business process. And especially at a time like this, Matt, like here we are, right? We have inflation, we have all of this
macroeconomic headwinds. Doing more with less is
perhaps more at a premium. And so if I find any
technology that allows us to be more productive, let's
take that and then let's create that economic surplus and then talk about how to distribute it in all the ways. And there are many, many
mechanisms one can talk about. - Well, I mean when you
talk about productivity, I'm gonna ask you about
productivity in general sense. But some people hear things like, we have to be more productive
and they think, right, with fewer human beings. So you're obviously very
optimistic, you obviously see it. What is, can you just
talk a little bit about what might be concerning
or cautionary about it as it becomes more widely adopted? - Yeah, I mean I think the point is if there's more automation, and take even what's happening
with tech jobs today? Interestingly enough, if you look at it, there was as tech supply
in what is considered the tech industry is now sort of basically getting more distributed because every auto company,
every pharma company, every retail company
needs to hire tech people. So to some degree, we should not think about
automation in one company to mean that that person
is not required elsewhere. And so the question is what are, what is the overall capacity
for the economy and society to absorb and create new jobs? And that I think is going to be the real. And then the other thing
that we should also have is wage support for different jobs. I've always felt like why is
there such disparity today in the job, in the labor market between
let's say some care worker and let's call it sort
of a software developer. And it's because we think of, we as a society have decided
to give it different, I'd say premium. Those premiums will adjust
as some of these technologies really truly get diffused. - Well, the diffusion seems key when I think about the theme this here at Davos of fractionalization, and there's a lot of
talk in the hallways here about the new globalization, the implication of the
technology obviously go beyond national borders quite
quickly and quite dramatically when you talk about the
impact you see in India, it's not just software jobs
moving from Silicon Valley to Boise, Idaho, but really potentially everywhere around the world very quickly here. - Yeah, I mean look, the idea that every country
has to have social cohesion based on the jobs and
the economic opportunity, I think is much better
understood today than, let's call it the first
phase of globalization. Whatever happens in the sort of this phase of globalization is
not gonna repeat the mistakes of the previous era where when there is displacement
happening in a society, I think everybody's gonna focus on what do we do about those people
who are getting displaced, getting trained, getting new jobs. So I think now we have to, in some sense, to your point, really
account for both forces. A globalization force, you know, David Ricardo was not wrong. There is going to be
competitive advantage of nations and things will still exist where there is a reason why people will wanna globalize,
but at the same time, every politician gets elected
because of local politics and they want to care a lot
more about jobs locally. And so therefore, in fact,
that's the right balance to have. - Last question on this, we wanna talk about a few other things, but it's a bit hypothetical, of course, particularly given the scale
of change of the technology. But have you wrapped your head
around it as you look at it, if you thought about a
company like Microsoft five years from now, 10 years from now, what this widespread adoption
of the technology of Chat GPT means for how you're organized,
how you're structured, how you do work, what the real actual
implications are gonna be on the ground. Have you been able to think
that through very much? And when you look ahead, what do you see? - Absolutely. I mean this is the, one of the
hardest things that you learn in a tech company. You know, we are what, 48 years old today. And it's hard because you have to adjust, the means of production essentially in our tech business changed dramatically. And that it requires us
to unlearn and learn, which is always very
unforgiving, quite frankly. And if you look at what
even these large models or foundational models
are, it's very different. In fact, I would say one of the things that is perhaps the toughest thing is the previous era AI expert is the one that is gonna have the
hardest time shifting to this new paradigm because everything, all the assumptions, oh
my God, here's my data, I'm gonna train on that data. My data is the only thing that matters. All that's now questioned, you now have a large
model which can be used as a retrieval engine on your data that's gonna perform better than sort of what something that you
trained on your data. I mean, just the intuition, just so that people have what this is, is suppose you train
a model on, let's say, all the math formulas. Yeah, it'll get pretty efficient in math. But let's say you train a
model on all the math formulas and all the human text
there is on the web, it gets better at math. And you say, why? How is that possible? Of course it's possible
because when we went to school, it's not like we just learned
math, we learned math, we learned history, we learned language. And so yeah, so something, so that emergent capability
is a pretty different thing than like why we were
even a couple of years ago as state of the art in terms of AI. - Do we need to learn math anymore? Why learn math? - Lemme tell you, I'm an electrical engineer who never understood
the Maxwell's equations. So now I finally get, thanks to Chat GPT, a better understanding of it. So I think one of the
things is we will all enjoy a lot more math because we will
have that personalized tutor who will, in fact, be able to
intervene at the crucial time when you're making a conceptual
mistake and help you learn. So just imagine that, just Matt, what if there was a
fantastic tutor teacher for every student learning
math going forward, that is now possible. - Okay. I'm gonna break my word 'cause I wanted to ask you one more thing, which I, on this then we'll move on, which is short term, I think we have a story that
I think is coming today, just that in the short term, you guys are making more
tools available through at Microsoft with the AI. How will we see it affect Microsoft and our engagement with
Microsoft in the near term? Just talk a little bit
about what your plan- - Yeah, I mean, look at Microsoft. The one thing that I think
it's probably worth stating is this thing just happen that is Chat GPT and GPT family of models. This is something that
we've been partnered with OpenAI deeply now for multiple years, and we built in Azure, our public cloud infrastructure,
an AI supercomputer, which, by the way, as
a systems architecture has been a massive breakthrough because the way these workloads or the way you train large
models is very different than anything out there. It's a much more large scale
synchronous distributed job. So we had to build the system from storage to compute to network
that really allowed us to even build this capability. So I think at this point, the way Microsoft's going
to really commercialize all of this is Azure has
become the place for anybody and everybody who thinks about
AI and large scale training. And we are way ahead on
that and we continue to plan to sort of really step it up there. Second, is we are gonna make these foundational models
available as platforms. So that means anybody who
wants to build on them in any domain can build on top of that. - [Matt] Soon, soon. - Soon, in fact, today we just
made the Azure OpenAI service available generally,
and then even Chat GPT will be available as an API. And so we are very,
very excited about that. And then we will incorporate
this in our own application. So you can fully expect us to obviously every product of Microsoft will have some of the same AI capabilities to completely transform the product. - Okay, so we'll be seeing it soon. Let me hit on a couple other
topics while I've got you. So productivity, you've
mentioned a couple of times in relation to AI, but more broadly, you've been talking a
lot about productivity in this workplace moment,
Microsoft, which we should say has certainly has a good
business of remote work and helping facilitate it. But you've sort of suggested
that from your research, work from home is not necessarily as unproductive as many
bosses are saying that it is. But at the same time,
you've also wanted more, some presence of people in the office. What's the balance in your mind
now for being in the office, being at home and maximizing productivity, but still having a healthy
culture and connectivity, what's right for you, do you think? - Yeah, I mean, look, there is, there are three things at
least we observe in the data that we are at in aggregate that we use to even inform our own set of policies. The first is what you reference,
which is there is this, what I would call paranoia
around productivity, right? Every boss thinks that somehow they're not being as productive, every person working thinks
that they're burnt out. So there is this dichotomy
of at least how people feel. And I think the only way out
of that is to have data, right? Not dogma, which is, you know, ultimately we are all gonna be
responsible for the outcomes and if we are managing to the outcomes, then we'll be better off. So that's sort of one side of it. The second thing I
would say is we also all have to recognize that
people come for other people not for policy. Just because I said that
everyone needs to be at work, you know, it's just not gonna matter. But I think we all have to
learn some new soft skills as leaders and managers
where convening people, like if I say I have a
meeting or I have an event and make that event exciting. I think I would say, I say like the new management
technique is all of us are event managers, and I think that's, so we'll have to learn many
new soft tech, you know, soft management techniques in
order to get people to connect with people because it's important. - So go ahead finish it. - And then the last thing I'd say is even recruitment, right,
which is one of the things that, it is fascinating to see, like people wanna feel
connected to the company, its culture and also feel
that they're making progress. And so we have to go back
in the last three years, a lot of what we assumed
was happening on campus, so to speak, it was implicit. Now you have to make it
explicit, like what training, the connection with the managers, all of those things are really things where both digital tools
and explicit management time would be required. - So if I were a senior
executive at Microsoft and you were my direct supervisor, how often would you want
to see my face in person. - You know, as often as I wanted to. (audience laughing)
So, but the thing that, that is the key I think
is like for what purpose? In fact, I think we are all increasingly when Peter and you ask somebody
where are you traveling to, people think about like,
what am I traveling for? What is the purpose? If I come into work, what do I wanna do? So I think being a little more deliberate about things that you do while
exercising your flexibility, I think is what's gonna have to happen. - And one other point on
this for you as a boss, I think one of the complaints you hear, put the productivity thing to the side, is it's harder to know
what everybody's doing, harder to have that sense or to measure some of those things. And of course there are intangibles that you can't quite
measure with data, exactly. So do you feel that tension and stress because you've got a
more diffuse organization with people in different locations? - The biggest, interesting to your point, I think you're right in saying
that the productivity data, in fact, I see like when
I'm on a teams meeting, I actually meet more people
than in a physical meeting because guess what? I can click on their profile, I know who they are, I can
go to their LinkedIn profile, I looked them up. I know more and more people in
chat on teams are commenting in addition to what somebody's speaking. So in some sense, the multimodal side of it, I miss it sometimes in-person meetings, that doesn't mean the in-person meeting doesn't have its own advantage. - Mm.
- Which is I have a side conversation, I walk out with somebody from a meeting. So I think we are all learning how to use both these sets of capabilities
and tools to maximize, and I don't think it's
one versus the other. So I don't think there's
any going back to 2019, but at the same time, it's not like we are gonna be working as if we are in 2020. And I think that that combination is what we are all trying to crack. - I'm gonna go out for a couple questions from the crowd in one second. I'm gonna ask you one
thing before I do that, I just wanted to get everybody ready and then I know you're gonna have to run, but I can't not ask you about Activision. The FTC is sued to stop the purchase. You and Brad Smith have expressed
optimism about the deal. There was a report from
a competitor of ours, Reuters yesterday that the EU is looking at challenging the deal. Realistically, and I know you publicly are expressing optimism about it. What's the timeframe for
a make or break point on really pursuing this deal in your mind? And are there conditions that just would make it
impossible to pursue? - Look, I mean the, being whatever, a number
four player trying to add some content and
create more opportunity for more publishers, more
gamers to be able to enjoy the- - I don't think Leader Khan
is watching the livestream. I have to warn you about. - I mean, it's like if you
believe in competition, you should believe in this deal. And I think the, you know, the fact that people who
don't even make games are the largest extractors
of rents in gaming, shouldn't that tell the regulators that where they should be looking. It's unbelievable to me how,
you know, shortsighted some of, I would say the way people
look at competition is, and in fact, I hope the competition
authorities get focused more on competition and that'll be a good day. - Okay. Question right here. - [Keith] Hi Satya. Keith Ferrazzi. Oh hi Keith Ferrazzi. I run a research institute
on the future of hybrid work. It's very frustrating that
fewer than 15% of your peers during this amazing remote
laboratory that they had for two years actually looked
at reinventing how they work. And they still debate
where they're working, but they haven't used your
extraordinary tech stack to actually reinvent the work. What can you do to build a movement that allows all the tools you have to actually get used when
reality organizations are merely scratching the surface? - I mean, I think it's like, it looks like what you are doing. (Matt giggles) I mean, quite honestly, I think the, I think it's a great
point, which is what's the, if you take go back to something like business
process re-engineering in the early '90s, there was very important to have essentially a
management doctrine even in order to help people
deploy the ERP systems and what have you. So the question is what
is the sophistication of the sort of modern work
doctrine, so to speak, that is much more widely
spread across all teams. And so that's, I think what
everybody's understanding and this is where the complexity
here is we have refined, as somebody said, the best collaboration
tool we have all developed is the workplace for 200 plus years. And so to suddenly say let's go add to it is sort of a tough challenge. And so, but that's the challenge. I think we have to learn
the management techniques, like even how to hold
a meeting going forward where there are two people
remote and nine people, say, in the meeting. The expectations of those two people are very different today
than they were two years ago. They're not going to deal
with anything second class. And so if you as a leader
don't have the skills on how to incorporate them appropriately, you're gonna have a bad meeting. And so I think that that
understanding, like, you know, it's not like the thing that
you learn when you join, but I think people who are
growing up as leaders today, and you know workers today are going to learn that inherently. And so it's a generational change. - Gentlemen, right there, the white shirt. Okay, this way next. - [Philip] Thank you, Satya. I'm Philippe Monnier, I'm representative of a
Swiss startup called WayRay specialized in augmented reality. I have a question. What do you think will
be the impact of GPT on newspaper, in particular
on the Wall Street Journal? (Matt laughs)
(audience laughing) - I think they'll be able
to write great articles going into the future using GPT. - I think we all know that
currently no news organization relies on formula writing at all. So, okay. I'll take the gentleman
back there on stand, right? Yes, yes, go ahead. - I'll speak up loud.
- Okay. - Mishal Kapoor, you talked a lot about AI and its productivity and its role in digital transformation. What is your opinion on blockchain? The technology rather than the news? - Look, I mean, I'm neutral to it, right? Which is it's a technology
that has a set of use cases and we support it today. And even a distributed
database is a good thing. It has its users. I think the entirety of that
space we have not yet found, like in the context the
difference between, I would say, all this Web3 and AI and
quite frankly even Metaverse is all of these three things
are all going to happen, but you need to have the killer apps. What is the use case
that gets broad adoption? What's the Chat GPT moment on blockchain? When I first sort of had, you know, got to know the web, it
was through, you know, the Mosaic browser, I think
all of us remember like, I think at least the difficulty I have in some of these other
technologies, what's the moment? Like even on the metaverse,
that's why I'm very, very keen even at WEF we are, you know, the Global Collaboration Village and Mesh. That's the stuff, right? Which is, if we can start saying, hey, this is just the next
generation of presence, here is how teams will evolve
to include more presence and then we are all using
it and it's mainstream, then we'll know that moment has arrived. So I think we have to keep pushing, I believe in all of these
technologies and it's up to us on the technology side to make
it more real for more people.
MS Word's handy autofill thing is about to get a lot more helpful
he circumvents so many of the interviewers questions
I wonder if Google Docs and OpenOffice will respond in kind. The last thing we need is another Microsoft monopoly.
About to get ClippyGPT