Speaker 1: Microsoft has been working on AI for decades and chatnots
Speaker 1: actually aren't anything new, but all of a sudden everyone
Speaker 1: is salivating. Why do you think the moment for AI
Speaker 1: is now? Yeah, I mean it's actually you're absolutely right,
Speaker 1: which is AI has been here in fact its mainstream, right,
Speaker 1: I mean, search is an AI product, even the current
Speaker 1: generation of search, every news aggregation, recommendation, and you know
Speaker 1: YouTube or e commerce or TikTok or all AI products,
Speaker 1: except they're all I would say, today's generation of AI
Speaker 1: is all autopilot. In fact, it's a black box that
Speaker 1: beaches sort of use that is dictating in fact, how
Speaker 1: our attention is focused. Whereas going forward, the thing that's
Speaker 1: most exciting about this generation of AI is perhaps we
Speaker 1: move from autopilot to copilot, where we actually prompted. I mean,
Speaker 1: think about it, right, what we are learning to program
Speaker 1: AI as with just natural language, right, and it gets
Speaker 1: smarter every time you use it. Yeah yeah, and also
Speaker 1: you are making it. It's just it's ultimately a stochastic
Speaker 1: machine that you're using as a tool to help reason
Speaker 1: about what you're learning, what you're creating, what you're doing.
Speaker 1: And so yes, I think this shift from autopilot to
Speaker 1: copilot is actually, yes, the next phase of AI, which
Speaker 1: in fact is perhaps going to put us as humans,
Speaker 1: you know, more in the center of using AI to
Speaker 1: our benefit. With Copilot, you are deeply weaving lams across
Speaker 1: all of Microsoft's products Word, Excel, power Point, Outlook. You're
Speaker 1: also basically giving folks their own personal business chatbot. How
Speaker 1: transformative a change do you think this will be in
Speaker 1: how we work? Yeah? To me, that is it right.
Speaker 1: Having built now up Copilot, having built the web co
Speaker 1: pilot with being, and even what we did with Dynamic,
Speaker 1: this is the big next step for us to put
Speaker 1: it in the tools everybody uses every day for their work.
Speaker 1: I think it does three things emily for me. You know,
Speaker 1: one of the things that I've always said is, God,
Speaker 1: there's so much functionality in Word or Excel and PowerPoint.
Speaker 1: How do we make it such that people use this
Speaker 1: in powerful ways to create great content, great documents, great
Speaker 1: PowerPoint art, learn how to do analysis that's pretty sophisticated
Speaker 1: in an interesting way. Now without having to say, let
Speaker 1: me learn all the commanding of office, I just literally
Speaker 1: can use natural language. So the power of thirty plus
Speaker 1: years of office creation, the sophistication of these tools is
Speaker 1: just available to every user. Same thing with even teams
Speaker 1: and teams co pilot. I think about how meetings can
Speaker 1: be more effective team's co pilot, But I think the
Speaker 1: probably the biggest difference maker will be business chat because
Speaker 1: if you think about the most important database in any
Speaker 1: company is the database underneath all of your productivity software.
Speaker 1: Accept that data is all siloed today, But now I
Speaker 1: can queriate with natural I can say, oh, I'm going
Speaker 1: to meet this customer. Can you tell me the last
Speaker 1: time I met them? Can you bring up all the
Speaker 1: documents that are written up about this customer and summarize
Speaker 1: it so that I'm current on what I need to
Speaker 1: be prepped for that ability to interrogate that database, queriate
Speaker 1: and do it without learning some new syntax of querying language.
Speaker 1: But just natural language is super powerful. How do you
Speaker 1: make sure it's not clippy two? Point out that it
Speaker 1: is helpful, delightful, doesn't want to make me click out
Speaker 1: a sap. There are two sets of things. One is
Speaker 1: you know if you're laughing, because because look like our
Speaker 1: industry is full of lots of you know, examples from
Speaker 1: clippy to even let's a current generation of these assistants
Speaker 1: and so on, they all griddle. I think there are
Speaker 1: two things that this generation of way I do. One
Speaker 1: is when we say they understand natural language, they truly
Speaker 1: understand natural language. So it's not like, Okay, we'll understand
Speaker 1: you only if you stay in sort of these very
Speaker 1: narrow rails that we've defined for you. Then the comprehension
Speaker 1: and what they can do for you right is also
Speaker 1: not narrow, and so I think that's why. But that said,
Speaker 1: I think we are also going to have to learn
Speaker 1: that ultimately these are tools. They're stochastic in nature. Just
Speaker 1: like anytime somebody sends me a draft, I review the draft,
Speaker 1: I just don't accept the draft. We will do that
Speaker 1: like interesting enough, we learn a lot and get up
Speaker 1: co pilot. In fact, that first time we get up
Speaker 1: copiot came even softa abouper saying oh yeah, this does
Speaker 1: make mistakes, except in even a few months people say,
Speaker 1: oh yeah, but I know how to correct those mistakes.
Speaker 1: And so that ability to work with this co pilot,
Speaker 1: give it feedback, know how to verify it. Even this
Speaker 1: chain of thought, reasoning and excel. Like the one feature
Speaker 1: I don't know if you saw this, but that is
Speaker 1: very cool, which is we said, okay, what's the design
Speaker 1: choice we can make so the users get in the
Speaker 1: habit of not just accepting whatever AI is saying, but
Speaker 1: even ask it to show you it's scratch bad work. Right.
Speaker 1: It's literally like inspecting somebody's homework, right, which is, hey,
Speaker 1: tell me exactly how you did this and so that
Speaker 1: I can verify. Those are the kinds of things that
Speaker 1: we learn. You're trying to reinvent search with this AI
Speaker 1: powered thing, and I believe it's been using GPT for
Speaker 1: for a while. Now what's worked? What has it? I
Speaker 1: think what they're too. One thing that we're learning is
Speaker 1: the search context, right, So conversational search is a thing.
Speaker 1: So this grounding of your conversation with search data, I
Speaker 1: think is one mode. And then there is a completely
Speaker 1: different mode that we're also learned, which is people just
Speaker 1: want to chat. And so we are now getting good
Speaker 1: at even the product design so that we make that
Speaker 1: an explicit choice. So for example, when we launched Being,
Speaker 1: we didn't have these three modes. We now have how
Speaker 1: precise do you want it to be? Or how creative
Speaker 1: you want to be or you want to be? Balanced
Speaker 1: that I think is one of the biggest learnings we
Speaker 1: launched it at Oh Wow. People do, in fact want
Speaker 1: to engage even in what is chat inside of search
Speaker 1: in different ways, and we've got to put the user
Speaker 1: control back. How much market share do you think you
Speaker 1: can really take from Google? Like prediction? Give me. We
Speaker 1: are a real I'm thrilled to be in search. We're
Speaker 1: a very small player in search, and I look forward
Speaker 1: to every inch we gain is a big game. You're
Speaker 1: coming for Search, They're coming for Office. They're now putting
Speaker 1: AI in there. You know, Google Docs and cheets and Gmail.
Speaker 1: Are we just going to see you and Sundar are
Speaker 1: trying to one up each other every week in this
Speaker 1: race to greatness. You know, I just warnt bardon being
Speaker 1: both to thrive. I just want Google work Space and
Speaker 1: Microsoft three six five both to thrive. I mean, look,
Speaker 1: at the end of the day, the fun part of
Speaker 1: being in this industry and competing is but you know,
Speaker 1: it's the innovation and competition. Is the last time I
Speaker 1: checked off a fantastic thing for users and the industry,
Speaker 1: and so yeah, so let there be good sort of
Speaker 1: you know, good innovation coming. And I think you know,
Speaker 1: Google's going to do you know, is a very innovative
Speaker 1: company and uh, and we have a lot of respect
Speaker 1: for them, and I expect us to compete in multiple categories.
Speaker 1: In my decade plus covering Microsoft, I can't remember you
Speaker 1: releasing this much in quick succession. Why is it all
Speaker 1: happening so fast? Yeah, it's you know, it's sort of
Speaker 1: sometimes it feels it's all happening fast. It's we started
Speaker 1: working on this, you know, good four years ago, right,
Speaker 1: I mean in some sense, if you think about when
Speaker 1: open ai and Microsoft came together and said, hey, this
Speaker 1: next generation of large language models need infrastructure. Let's build
Speaker 1: the infrastructure, tune the infrastructure, Let's understand even what AI
Speaker 1: safety and alignment looks like for these what are the
Speaker 1: use cases? And this has been four years plus in making.
Speaker 1: So once we started seeing the scaling effects, the promise
Speaker 1: of the emergent capabilities, even that started showing up in
Speaker 1: these large language models. That's why last years in fact
Speaker 1: that perhaps for me, the application of these large language
Speaker 1: models inside or get up Copilot was the big it's
Speaker 1: the biggest LM product out there today, and so that
Speaker 1: gave us confidence that hey, we now can apply it
Speaker 1: in more context. So yes, it feels that we've launched
Speaker 1: a lot of things just in a hurry this year,
Speaker 1: but it's been four years in the making, and obviously
Speaker 1: it's a great partnership with open AI. Microsoft just reportedly
Speaker 1: laid off a team focused on ethical and responsible AI. Meantime,
Speaker 1: you've got the Center for Humane Technology calling the too
Speaker 1: AI a RaSE to recklessness. How do you respond to that?
Speaker 1: I mean, first of all, in terms of impact on
Speaker 1: anybody at Microsoft, this is just probably the thing that
Speaker 1: weighs on me heavily, because after all, any restructuring is hard,
Speaker 1: hard on the people who are mostly impacted. That said,
Speaker 1: two things. One is this is no longer a side
Speaker 1: thing for Microsoft, right because in some sense, whether it's design,
Speaker 1: whether it's alignment, safety, ethics, it's kind of like saying quality,
Speaker 1: performance and design, core design. So I can't have now
Speaker 1: an AI team on the side. It's all the mainstream.
Speaker 1: It's sort of like there's no get up. There's no
Speaker 1: get up without copilot. There is no Microsoft three six
Speaker 1: five without co pilot. So in some sense, the hard
Speaker 1: process of companies like ours are going to constantly go
Speaker 1: through a lot of change, and what you as something
Speaker 1: that was done on the side today is now mainstream.
Speaker 1: So that's what's happening. And then I think, if anything, debate,
Speaker 1: dialogue and scrutiny on what is the space of innovation?
Speaker 1: Is it really creating benefits for society? I think are absolutely,
Speaker 1: and I'll welcome it. Right, I look at them and say,
Speaker 1: no one can run faster than the benefits to the
Speaker 1: broader society. And then the norms that we enforce as
Speaker 1: a democratic society on any technology. And so I feel
Speaker 1: like we are at the very early stages of it.
Speaker 1: So I will ask us to be open to it,
Speaker 1: but at the same time scrutinize it and let's have
Speaker 1: a dialogue on what the benefits are. And in that context,
Speaker 1: let's also recognize, especially with this AI, well why were
Speaker 1: we not asking ourselves, like the AI that's already in
Speaker 1: our lives, and how what is it doing? It's right
Speaker 1: we've gone straight to say, oh, wow, these lns have
Speaker 1: some hallucination. Guess what. Right, there's a lot of AI
Speaker 1: that I don't even know what it's doing. And except
Speaker 1: I'm happily clicking away and accepting the recommendations. So why
Speaker 1: don't we in fact educate ourselves to ask all of
Speaker 1: what AI is doing in our lives and say how
Speaker 1: to do it safely in our line way. Elon Musk,
Speaker 1: who co found it open ai and then left, has
Speaker 1: said it's not what he intended. It is closed, sourced
Speaker 1: and effectively controlled by Microsoft. How would you respond? Look,
Speaker 1: I mean, I think, first of all, open ai cares
Speaker 1: deeply about their mission and doing it in the most
Speaker 1: safe way and in the most open way. And in
Speaker 1: some sense there's an interesting trade between openness and safety.
Speaker 1: So that is sort of one of the reasons why
Speaker 1: they have what they have in terms of their governance,
Speaker 1: architecture and you know, and so therefore at some level
Speaker 1: they have been very very clear on what principles drive them. Similarly,
Speaker 1: we have been very very clear on the principles that
Speaker 1: drive us around AI safety and responsibility, and we'll stick
Speaker 1: to them. I have to ask you a question about
Speaker 1: the economy and whether you're concerned about a prolonged tech bust.
Speaker 1: I mean, we've seen the collapse of three banks over
Speaker 1: the course of the last week, including Silicon Valley Bank,
Speaker 1: tighter money, more uncertainty. How are you thinking about this?
Speaker 1: I mean, I think at the highest or levels. I
Speaker 1: think there was an aberration of maybe a ten year
Speaker 1: period of low interest rates and everything that came with it,
Speaker 1: not just in tech but in the broader economy. And
Speaker 1: I just think that we're just getting back to normal,
Speaker 1: like at least the thing that perhaps we have to
Speaker 1: remind ourselves. Mostly the world looked like this, which is
Speaker 1: interest rates were higher than zero. Inflation was perhaps maybe
Speaker 1: structurally going to be higher, just given everything that's happening
Speaker 1: with supply chains in the geopolitics, and we all as
Speaker 1: businesses have to be accountable to how to manage in
Speaker 1: that environment, and tech is one sector. And so I
Speaker 1: kind of look at this and say, hey, it's a
Speaker 1: return to normal as opposed to anything sort of that
Speaker 1: to be we need to be worried about as being prolonged.
Speaker 1: In fact, this is the long run. The economies have
Speaker 1: to sort of be, you know, more real. All right,
Speaker 1: So this is normal to you, I think. So, I mean,
Speaker 1: I think that sometimes we sort of say, you know,
Speaker 1: the last ten years can never be sort of the
Speaker 1: way way forward on and it's good. I think it's
Speaker 1: better to have businesses that are run efficiently, that are
Speaker 1: actually measured on the way both whether it's on the
Speaker 1: societal impact or on real economic impact. In nineteen ninety five,
Speaker 1: Bill Gates Centemmo calling the Internet a title way if
Speaker 1: that would change all the rules and was going to
Speaker 1: be crucial to every part of the business, is AI
Speaker 1: and epic. Yeah. I mean, in fact, I sort of
Speaker 1: say the chat GPT when it first came out was
Speaker 1: like when Mosaic first came out I think in ninety
Speaker 1: three as the first browser. And so yes, it does
Speaker 1: feel like you know, to the Bill Memo in nineteen
Speaker 1: ninety five, It does feel like that to me. So
Speaker 1: it's as big as the enter. I think it's as big.
Speaker 1: It's just like in all of these things, right we
Speaker 1: in the tech industry or you know, classic experts and
Speaker 1: over hyping everything. So the question is can we really
Speaker 1: like I hope at least that What motivates me is
Speaker 1: I want to use this technology to truly do what
Speaker 1: I think at least all of us are in tech
Speaker 1: for which is democratizing access to it. So when someone
Speaker 1: says to me, hey, here is how a farmer in
Speaker 1: rural India, you know, can use this technology to express
Speaker 1: a complex thought on how to get a subsidy from
Speaker 1: a government program and can do that successfully. That gives
Speaker 1: me a lot of sort of you know, hope. How
Speaker 1: confident are you that Microsoft is going to catch the wave? Look?
Speaker 1: We are you know, at the end of the day,
Speaker 1: my confidence is high only if I can do useful
Speaker 1: things every day for users. So in other words, what
Speaker 1: we did with being, what we did with getub copilot,
Speaker 1: and what we're about to now do with Microsoft three
Speaker 1: six five copilot is what gives me confidence. Ultimately, it's
Speaker 1: not about my confidence, but it's about the products people
Speaker 1: use and find useful. I want to ask about jobs
Speaker 1: because obviously Microsoft makes software that helps people do their jobs,
Speaker 1: and I wonder if AI laid in software, we'll put
Speaker 1: some people out of jobs. Sam Altman has this idea
Speaker 1: that AI is going to create this kind of utopia
Speaker 1: and generate wealth that's going to be enough to cut
Speaker 1: everyone a decent size check, but eliminate some jobs. Do
Speaker 1: you agree with that? You know? Look, I mean you
Speaker 1: know from Kenes, do I guess? Altman? They've all talked
Speaker 1: about the two day work week, and I'm looking forward
Speaker 1: to it. But the point is, Look, the lump of
Speaker 1: labor fallacy has never proven out right, which is in
Speaker 1: some sense there is displacement, and in fact of anything,
Speaker 1: what we have to do is really do a fantastic
Speaker 1: job as a society to deal with any displacement. Because
Speaker 1: one job turns into another job, you have to then
Speaker 1: skill people on an other job. And in fact, in
Speaker 1: an interesting way, here's one thing even in this Microsoft
Speaker 1: three six five tool, like, there's this power automate tool.
Speaker 1: Up to now we've called it the low code no
Speaker 1: code tool for doing workflo automation. Interestingly enough, you now
Speaker 1: can automate workflows just using natural language. Guess what that means.
Speaker 1: Anybody who's in the front lines in healthcare and retail
Speaker 1: can automate or be part of the IT journey. That
Speaker 1: to me gives means their new jobs and better wage support.
Speaker 1: So I feel, yes, there's going to be some changes
Speaker 1: in jobs. There's going to be some places where there
Speaker 1: will be wage pressure, there will be opportunities for increased
Speaker 1: wages because of increased productivity. We should look at it
Speaker 1: all and at the same time being very clear eyed
Speaker 1: about any displacement risk because that one thing that we've
Speaker 1: also learned in the last twenty years is that any
Speaker 1: society that doesn't really pay attention to who are the
Speaker 1: winners and the losers, and to make sure that as
Speaker 1: a society we are not really you know, imbalanced in
Speaker 1: it in terms of economic opportunity, will be better off.
Speaker 1: I think a lot about my kids and how AI
Speaker 1: will have something that I don't, which is an infinite
Speaker 1: amount of time to spend with them, and how these
Speaker 1: chatpots are so friendly, and how quickly that could turn
Speaker 1: into an unhealthy relationship or you know, maybe it's nudging
Speaker 1: them to make a bad decision. As a parent, does
Speaker 1: any part of that scare you? So that's kind of
Speaker 1: one of the reasons why I think this moving from
Speaker 1: autopilot to this copilot hopefully gives us more control, whether
Speaker 1: it's as parents are more importantly, even as children. Like
Speaker 1: one of the things that was very cool yesterday to
Speaker 1: see in the launch of GPT four was the demo
Speaker 1: or the launch of Khan Academy stuff. And sal sent
Speaker 1: me this last night and I was looking at his
Speaker 1: algebra class. It was so engaging, right, I mean, think
Speaker 1: about it, like one of the dreams we've always had
Speaker 1: is can I have a personalized tutor that is engaging,
Speaker 1: that is actually trying to teach me so to yours point,
Speaker 1: I think maybe we should, of course be very very
Speaker 1: watchful of what happens. But at the same time, I
Speaker 1: think this generation of bots, in this generation of AI,
Speaker 1: probably just go from engagement to more giving us more
Speaker 1: agency to learn. It's fascinating such a NATA. Thank you,
Speaker 1: thank you for watching us.