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Speaker 1: Microsoft has been working on AI for decades and chatnots

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Speaker 1: actually aren't anything new, but all of a sudden everyone

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Speaker 1: is salivating. Why do you think the moment for AI

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Speaker 1: is now? Yeah, I mean it's actually you're absolutely right,

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Speaker 1: which is AI has been here in fact its mainstream, right,

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Speaker 1: I mean, search is an AI product, even the current

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Speaker 1: generation of search, every news aggregation, recommendation, and you know

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Speaker 1: YouTube or e commerce or TikTok or all AI products,

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Speaker 1: except they're all I would say, today's generation of AI

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Speaker 1: is all autopilot. In fact, it's a black box that

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Speaker 1: beaches sort of use that is dictating in fact, how

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Speaker 1: our attention is focused. Whereas going forward, the thing that's

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Speaker 1: most exciting about this generation of AI is perhaps we

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Speaker 1: move from autopilot to copilot, where we actually prompted. I mean,

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Speaker 1: think about it, right, what we are learning to program

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Speaker 1: AI as with just natural language, right, and it gets

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Speaker 1: smarter every time you use it. Yeah yeah, and also

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Speaker 1: you are making it. It's just it's ultimately a stochastic

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Speaker 1: machine that you're using as a tool to help reason

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Speaker 1: about what you're learning, what you're creating, what you're doing.

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Speaker 1: And so yes, I think this shift from autopilot to

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Speaker 1: copilot is actually, yes, the next phase of AI, which

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Speaker 1: in fact is perhaps going to put us as humans,

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Speaker 1: you know, more in the center of using AI to

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Speaker 1: our benefit. With Copilot, you are deeply weaving lams across

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Speaker 1: all of Microsoft's products Word, Excel, power Point, Outlook. You're

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Speaker 1: also basically giving folks their own personal business chatbot. How

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Speaker 1: transformative a change do you think this will be in

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Speaker 1: how we work? Yeah? To me, that is it right.

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Speaker 1: Having built now up Copilot, having built the web co

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Speaker 1: pilot with being, and even what we did with Dynamic,

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Speaker 1: this is the big next step for us to put

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Speaker 1: it in the tools everybody uses every day for their work.

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Speaker 1: I think it does three things emily for me. You know,

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Speaker 1: one of the things that I've always said is, God,

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Speaker 1: there's so much functionality in Word or Excel and PowerPoint.

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Speaker 1: How do we make it such that people use this

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Speaker 1: in powerful ways to create great content, great documents, great

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Speaker 1: PowerPoint art, learn how to do analysis that's pretty sophisticated

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Speaker 1: in an interesting way. Now without having to say, let

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Speaker 1: me learn all the commanding of office, I just literally

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Speaker 1: can use natural language. So the power of thirty plus

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Speaker 1: years of office creation, the sophistication of these tools is

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Speaker 1: just available to every user. Same thing with even teams

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Speaker 1: and teams co pilot. I think about how meetings can

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Speaker 1: be more effective team's co pilot, But I think the

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Speaker 1: probably the biggest difference maker will be business chat because

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Speaker 1: if you think about the most important database in any

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Speaker 1: company is the database underneath all of your productivity software.

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Speaker 1: Accept that data is all siloed today, But now I

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Speaker 1: can queriate with natural I can say, oh, I'm going

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Speaker 1: to meet this customer. Can you tell me the last

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Speaker 1: time I met them? Can you bring up all the

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Speaker 1: documents that are written up about this customer and summarize

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Speaker 1: it so that I'm current on what I need to

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Speaker 1: be prepped for that ability to interrogate that database, queriate

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Speaker 1: and do it without learning some new syntax of querying language.

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Speaker 1: But just natural language is super powerful. How do you

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Speaker 1: make sure it's not clippy two? Point out that it

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Speaker 1: is helpful, delightful, doesn't want to make me click out

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Speaker 1: a sap. There are two sets of things. One is

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Speaker 1: you know if you're laughing, because because look like our

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Speaker 1: industry is full of lots of you know, examples from

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Speaker 1: clippy to even let's a current generation of these assistants

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Speaker 1: and so on, they all griddle. I think there are

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Speaker 1: two things that this generation of way I do. One

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Speaker 1: is when we say they understand natural language, they truly

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Speaker 1: understand natural language. So it's not like, Okay, we'll understand

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Speaker 1: you only if you stay in sort of these very

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Speaker 1: narrow rails that we've defined for you. Then the comprehension

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Speaker 1: and what they can do for you right is also

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Speaker 1: not narrow, and so I think that's why. But that said,

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Speaker 1: I think we are also going to have to learn

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Speaker 1: that ultimately these are tools. They're stochastic in nature. Just

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Speaker 1: like anytime somebody sends me a draft, I review the draft,

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Speaker 1: I just don't accept the draft. We will do that

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Speaker 1: like interesting enough, we learn a lot and get up

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Speaker 1: co pilot. In fact, that first time we get up

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Speaker 1: copiot came even softa abouper saying oh yeah, this does

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Speaker 1: make mistakes, except in even a few months people say,

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Speaker 1: oh yeah, but I know how to correct those mistakes.

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Speaker 1: And so that ability to work with this co pilot,

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Speaker 1: give it feedback, know how to verify it. Even this

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Speaker 1: chain of thought, reasoning and excel. Like the one feature

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Speaker 1: I don't know if you saw this, but that is

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Speaker 1: very cool, which is we said, okay, what's the design

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Speaker 1: choice we can make so the users get in the

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Speaker 1: habit of not just accepting whatever AI is saying, but

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Speaker 1: even ask it to show you it's scratch bad work. Right.

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Speaker 1: It's literally like inspecting somebody's homework, right, which is, hey,

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Speaker 1: tell me exactly how you did this and so that

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Speaker 1: I can verify. Those are the kinds of things that

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Speaker 1: we learn. You're trying to reinvent search with this AI

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Speaker 1: powered thing, and I believe it's been using GPT for

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Speaker 1: for a while. Now what's worked? What has it? I

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Speaker 1: think what they're too. One thing that we're learning is

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Speaker 1: the search context, right, So conversational search is a thing.

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Speaker 1: So this grounding of your conversation with search data, I

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Speaker 1: think is one mode. And then there is a completely

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Speaker 1: different mode that we're also learned, which is people just

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Speaker 1: want to chat. And so we are now getting good

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Speaker 1: at even the product design so that we make that

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Speaker 1: an explicit choice. So for example, when we launched Being,

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Speaker 1: we didn't have these three modes. We now have how

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Speaker 1: precise do you want it to be? Or how creative

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Speaker 1: you want to be or you want to be? Balanced

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Speaker 1: that I think is one of the biggest learnings we

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Speaker 1: launched it at Oh Wow. People do, in fact want

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Speaker 1: to engage even in what is chat inside of search

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Speaker 1: in different ways, and we've got to put the user

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Speaker 1: control back. How much market share do you think you

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Speaker 1: can really take from Google? Like prediction? Give me. We

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Speaker 1: are a real I'm thrilled to be in search. We're

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Speaker 1: a very small player in search, and I look forward

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Speaker 1: to every inch we gain is a big game. You're

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Speaker 1: coming for Search, They're coming for Office. They're now putting

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Speaker 1: AI in there. You know, Google Docs and cheets and Gmail.

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Speaker 1: Are we just going to see you and Sundar are

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Speaker 1: trying to one up each other every week in this

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Speaker 1: race to greatness. You know, I just warnt bardon being

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Speaker 1: both to thrive. I just want Google work Space and

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Speaker 1: Microsoft three six five both to thrive. I mean, look,

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Speaker 1: at the end of the day, the fun part of

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Speaker 1: being in this industry and competing is but you know,

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Speaker 1: it's the innovation and competition. Is the last time I

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Speaker 1: checked off a fantastic thing for users and the industry,

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Speaker 1: and so yeah, so let there be good sort of

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Speaker 1: you know, good innovation coming. And I think you know,

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Speaker 1: Google's going to do you know, is a very innovative

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Speaker 1: company and uh, and we have a lot of respect

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Speaker 1: for them, and I expect us to compete in multiple categories.

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Speaker 1: In my decade plus covering Microsoft, I can't remember you

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Speaker 1: releasing this much in quick succession. Why is it all

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Speaker 1: happening so fast? Yeah, it's you know, it's sort of

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Speaker 1: sometimes it feels it's all happening fast. It's we started

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Speaker 1: working on this, you know, good four years ago, right,

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Speaker 1: I mean in some sense, if you think about when

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Speaker 1: open ai and Microsoft came together and said, hey, this

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Speaker 1: next generation of large language models need infrastructure. Let's build

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Speaker 1: the infrastructure, tune the infrastructure, Let's understand even what AI

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Speaker 1: safety and alignment looks like for these what are the

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Speaker 1: use cases? And this has been four years plus in making.

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Speaker 1: So once we started seeing the scaling effects, the promise

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Speaker 1: of the emergent capabilities, even that started showing up in

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Speaker 1: these large language models. That's why last years in fact

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Speaker 1: that perhaps for me, the application of these large language

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Speaker 1: models inside or get up Copilot was the big it's

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Speaker 1: the biggest LM product out there today, and so that

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Speaker 1: gave us confidence that hey, we now can apply it

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Speaker 1: in more context. So yes, it feels that we've launched

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Speaker 1: a lot of things just in a hurry this year,

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Speaker 1: but it's been four years in the making, and obviously

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Speaker 1: it's a great partnership with open AI. Microsoft just reportedly

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Speaker 1: laid off a team focused on ethical and responsible AI. Meantime,

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Speaker 1: you've got the Center for Humane Technology calling the too

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Speaker 1: AI a RaSE to recklessness. How do you respond to that?

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Speaker 1: I mean, first of all, in terms of impact on

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Speaker 1: anybody at Microsoft, this is just probably the thing that

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Speaker 1: weighs on me heavily, because after all, any restructuring is hard,

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Speaker 1: hard on the people who are mostly impacted. That said,

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Speaker 1: two things. One is this is no longer a side

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Speaker 1: thing for Microsoft, right because in some sense, whether it's design,

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Speaker 1: whether it's alignment, safety, ethics, it's kind of like saying quality,

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Speaker 1: performance and design, core design. So I can't have now

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Speaker 1: an AI team on the side. It's all the mainstream.

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Speaker 1: It's sort of like there's no get up. There's no

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Speaker 1: get up without copilot. There is no Microsoft three six

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Speaker 1: five without co pilot. So in some sense, the hard

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Speaker 1: process of companies like ours are going to constantly go

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Speaker 1: through a lot of change, and what you as something

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Speaker 1: that was done on the side today is now mainstream.

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Speaker 1: So that's what's happening. And then I think, if anything, debate,

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Speaker 1: dialogue and scrutiny on what is the space of innovation?

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Speaker 1: Is it really creating benefits for society? I think are absolutely,

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Speaker 1: and I'll welcome it. Right, I look at them and say,

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Speaker 1: no one can run faster than the benefits to the

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Speaker 1: broader society. And then the norms that we enforce as

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Speaker 1: a democratic society on any technology. And so I feel

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Speaker 1: like we are at the very early stages of it.

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Speaker 1: So I will ask us to be open to it,

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Speaker 1: but at the same time scrutinize it and let's have

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Speaker 1: a dialogue on what the benefits are. And in that context,

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Speaker 1: let's also recognize, especially with this AI, well why were

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Speaker 1: we not asking ourselves, like the AI that's already in

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Speaker 1: our lives, and how what is it doing? It's right

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Speaker 1: we've gone straight to say, oh, wow, these lns have

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Speaker 1: some hallucination. Guess what. Right, there's a lot of AI

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Speaker 1: that I don't even know what it's doing. And except

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Speaker 1: I'm happily clicking away and accepting the recommendations. So why

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Speaker 1: don't we in fact educate ourselves to ask all of

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Speaker 1: what AI is doing in our lives and say how

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Speaker 1: to do it safely in our line way. Elon Musk,

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Speaker 1: who co found it open ai and then left, has

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Speaker 1: said it's not what he intended. It is closed, sourced

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Speaker 1: and effectively controlled by Microsoft. How would you respond? Look,

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Speaker 1: I mean, I think, first of all, open ai cares

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Speaker 1: deeply about their mission and doing it in the most

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Speaker 1: safe way and in the most open way. And in

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Speaker 1: some sense there's an interesting trade between openness and safety.

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Speaker 1: So that is sort of one of the reasons why

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Speaker 1: they have what they have in terms of their governance,

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Speaker 1: architecture and you know, and so therefore at some level

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Speaker 1: they have been very very clear on what principles drive them. Similarly,

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Speaker 1: we have been very very clear on the principles that

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Speaker 1: drive us around AI safety and responsibility, and we'll stick

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Speaker 1: to them. I have to ask you a question about

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Speaker 1: the economy and whether you're concerned about a prolonged tech bust.

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Speaker 1: I mean, we've seen the collapse of three banks over

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Speaker 1: the course of the last week, including Silicon Valley Bank,

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Speaker 1: tighter money, more uncertainty. How are you thinking about this?

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Speaker 1: I mean, I think at the highest or levels. I

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Speaker 1: think there was an aberration of maybe a ten year

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Speaker 1: period of low interest rates and everything that came with it,

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Speaker 1: not just in tech but in the broader economy. And

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Speaker 1: I just think that we're just getting back to normal,

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Speaker 1: like at least the thing that perhaps we have to

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Speaker 1: remind ourselves. Mostly the world looked like this, which is

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Speaker 1: interest rates were higher than zero. Inflation was perhaps maybe

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Speaker 1: structurally going to be higher, just given everything that's happening

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Speaker 1: with supply chains in the geopolitics, and we all as

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Speaker 1: businesses have to be accountable to how to manage in

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Speaker 1: that environment, and tech is one sector. And so I

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Speaker 1: kind of look at this and say, hey, it's a

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Speaker 1: return to normal as opposed to anything sort of that

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Speaker 1: to be we need to be worried about as being prolonged.

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Speaker 1: In fact, this is the long run. The economies have

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Speaker 1: to sort of be, you know, more real. All right,

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Speaker 1: So this is normal to you, I think. So, I mean,

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Speaker 1: I think that sometimes we sort of say, you know,

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Speaker 1: the last ten years can never be sort of the

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Speaker 1: way way forward on and it's good. I think it's

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Speaker 1: better to have businesses that are run efficiently, that are

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Speaker 1: actually measured on the way both whether it's on the

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Speaker 1: societal impact or on real economic impact. In nineteen ninety five,

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Speaker 1: Bill Gates Centemmo calling the Internet a title way if

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Speaker 1: that would change all the rules and was going to

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Speaker 1: be crucial to every part of the business, is AI

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Speaker 1: and epic. Yeah. I mean, in fact, I sort of

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Speaker 1: say the chat GPT when it first came out was

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Speaker 1: like when Mosaic first came out I think in ninety

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Speaker 1: three as the first browser. And so yes, it does

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Speaker 1: feel like you know, to the Bill Memo in nineteen

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Speaker 1: ninety five, It does feel like that to me. So

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Speaker 1: it's as big as the enter. I think it's as big.

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Speaker 1: It's just like in all of these things, right we

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Speaker 1: in the tech industry or you know, classic experts and

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Speaker 1: over hyping everything. So the question is can we really

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Speaker 1: like I hope at least that What motivates me is

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Speaker 1: I want to use this technology to truly do what

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Speaker 1: I think at least all of us are in tech

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Speaker 1: for which is democratizing access to it. So when someone

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Speaker 1: says to me, hey, here is how a farmer in

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Speaker 1: rural India, you know, can use this technology to express

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Speaker 1: a complex thought on how to get a subsidy from

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Speaker 1: a government program and can do that successfully. That gives

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Speaker 1: me a lot of sort of you know, hope. How

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Speaker 1: confident are you that Microsoft is going to catch the wave? Look?

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Speaker 1: We are you know, at the end of the day,

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Speaker 1: my confidence is high only if I can do useful

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Speaker 1: things every day for users. So in other words, what

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Speaker 1: we did with being, what we did with getub copilot,

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Speaker 1: and what we're about to now do with Microsoft three

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Speaker 1: six five copilot is what gives me confidence. Ultimately, it's

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Speaker 1: not about my confidence, but it's about the products people

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Speaker 1: use and find useful. I want to ask about jobs

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Speaker 1: because obviously Microsoft makes software that helps people do their jobs,

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Speaker 1: and I wonder if AI laid in software, we'll put

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Speaker 1: some people out of jobs. Sam Altman has this idea

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Speaker 1: that AI is going to create this kind of utopia

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Speaker 1: and generate wealth that's going to be enough to cut

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Speaker 1: everyone a decent size check, but eliminate some jobs. Do

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Speaker 1: you agree with that? You know? Look, I mean you

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Speaker 1: know from Kenes, do I guess? Altman? They've all talked

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Speaker 1: about the two day work week, and I'm looking forward

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Speaker 1: to it. But the point is, Look, the lump of

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Speaker 1: labor fallacy has never proven out right, which is in

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Speaker 1: some sense there is displacement, and in fact of anything,

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Speaker 1: what we have to do is really do a fantastic

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Speaker 1: job as a society to deal with any displacement. Because

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Speaker 1: one job turns into another job, you have to then

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Speaker 1: skill people on an other job. And in fact, in

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Speaker 1: an interesting way, here's one thing even in this Microsoft

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Speaker 1: three six five tool, like, there's this power automate tool.

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Speaker 1: Up to now we've called it the low code no

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Speaker 1: code tool for doing workflo automation. Interestingly enough, you now

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Speaker 1: can automate workflows just using natural language. Guess what that means.

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Speaker 1: Anybody who's in the front lines in healthcare and retail

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Speaker 1: can automate or be part of the IT journey. That

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Speaker 1: to me gives means their new jobs and better wage support.

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Speaker 1: So I feel, yes, there's going to be some changes

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Speaker 1: in jobs. There's going to be some places where there

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Speaker 1: will be wage pressure, there will be opportunities for increased

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Speaker 1: wages because of increased productivity. We should look at it

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Speaker 1: all and at the same time being very clear eyed

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Speaker 1: about any displacement risk because that one thing that we've

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Speaker 1: also learned in the last twenty years is that any

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Speaker 1: society that doesn't really pay attention to who are the

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Speaker 1: winners and the losers, and to make sure that as

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Speaker 1: a society we are not really you know, imbalanced in

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Speaker 1: it in terms of economic opportunity, will be better off.

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Speaker 1: I think a lot about my kids and how AI

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Speaker 1: will have something that I don't, which is an infinite

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Speaker 1: amount of time to spend with them, and how these

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Speaker 1: chatpots are so friendly, and how quickly that could turn

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Speaker 1: into an unhealthy relationship or you know, maybe it's nudging

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Speaker 1: them to make a bad decision. As a parent, does

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Speaker 1: any part of that scare you? So that's kind of

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Speaker 1: one of the reasons why I think this moving from

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Speaker 1: autopilot to this copilot hopefully gives us more control, whether

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Speaker 1: it's as parents are more importantly, even as children. Like

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Speaker 1: one of the things that was very cool yesterday to

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Speaker 1: see in the launch of GPT four was the demo

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Speaker 1: or the launch of Khan Academy stuff. And sal sent

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Speaker 1: me this last night and I was looking at his

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Speaker 1: algebra class. It was so engaging, right, I mean, think

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Speaker 1: about it, like one of the dreams we've always had

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Speaker 1: is can I have a personalized tutor that is engaging,

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Speaker 1: that is actually trying to teach me so to yours point,

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Speaker 1: I think maybe we should, of course be very very

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Speaker 1: watchful of what happens. But at the same time, I

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Speaker 1: think this generation of bots, in this generation of AI,

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Speaker 1: probably just go from engagement to more giving us more

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Speaker 1: agency to learn. It's fascinating such a NATA. Thank you,

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Speaker 1: thank you for watching us.