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Speaker 1: AI, in Apple's view, can be used to this incredibly

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Speaker 1: empowering thing. But there is a sense that things are

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Speaker 1: changing very fast in ways that I think it's hard

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Speaker 1: for any normal person to keep up with. And while

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Speaker 1: I think we can look at this as you know,

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Speaker 1: yet another thing of the scale of the Industrial Revolution,

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Speaker 1: which changed our world in a giant way that displaced

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Speaker 1: a lot of people in the process, and still occurred

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Speaker 1: over like eighty years, and now this is happening in

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Speaker 1: a compressed time frame, and so I think it's fair

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Speaker 1: for people to say, Wow, I'm not quite certain what

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Speaker 1: this is going.

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Speaker 2: To mean for me.

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Speaker 3: I'm Laur Siegel, and you're listening to Mostly Human, a

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Speaker 3: tech podcast through a human.

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Speaker 4: Lens, Craig and Jaws.

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Speaker 3: I'm so happy to be sitting here with y'all. So

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Speaker 3: to give context to the folks who are listening. You

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Speaker 3: are chief of Software, chief of Marketing, very fancy titles.

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Speaker 3: I want to start specifically with what I think so

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Speaker 3: many folks have been thinking about, which is.

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Speaker 4: Apple and artificial intelligence.

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Speaker 3: When I was watching you, Craig on stage, there was

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Speaker 3: one line I wrote down that you said that I

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Speaker 3: thought was really interesting because there's been so much anticipation

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Speaker 3: about Apple and AI, and you said that some developers

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Speaker 3: seem to be racing to develop AI for the sake

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Speaker 3: of AI without thinking of people. And then you said,

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Speaker 3: truly helpful AI must be centered around you. So I thought,

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Speaker 3: maybe starting the conversation with what does AI centered around

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Speaker 3: me actually mean?

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Speaker 4: What does that look like?

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Speaker 1: Well, I think that's central to who Apple always is

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Speaker 1: around everything we do. I mean, if you think going

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Speaker 1: back to the beginnings of this company, there were these

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Speaker 1: nascent technology in the form of microprocessors, and our founder said,

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Speaker 1: how can we make something useful out of this?

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Speaker 2: Useful to people?

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Speaker 1: And then you look at graphical user interfaces and mobility

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Speaker 1: with iPhone and all of this is where there's all

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Speaker 1: this technological possibility out there, and initially it's used by

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Speaker 1: the people trying to figure out what is this all for?

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Speaker 1: What does this mean to people? And I think for Apple,

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Speaker 1: the question is, don't say I've got a hammer and

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Speaker 1: let me look for nail. Think about start with the

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Speaker 1: person and their experience and how you could make their

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Speaker 1: lives better, and then look for the things that could

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Speaker 1: enable that and build useful experiences out of that. And

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Speaker 1: that's what for us AI is another one of those

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Speaker 1: capabilities that fulfills all of these things that we've wanted

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Speaker 1: to do for so long in designing these experiences, but

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Speaker 1: where that ability for the system, the machine to really

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Speaker 1: understand you and what you were trying to accomplish was

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Speaker 1: only so capable, And now there's this leap in capability,

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Speaker 1: and so now it can connect with things that we

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Speaker 1: think we've always wanted our phone and our iPads and

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Speaker 1: our max to do for us, and we know that

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Speaker 1: our customers feel the same way, and now we're trying

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Speaker 1: to bring that to them.

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Speaker 2: But that's where it starts.

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Speaker 1: It starts at what's something that matters to you, you

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Speaker 1: that would make your day a little bit better, let

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Speaker 1: you feel a little.

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Speaker 2: Bit more empowered.

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Speaker 1: And if we can bring this technology to bear on

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Speaker 1: that problem, that's a that's a wonderful role for.

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Speaker 5: Apple to play.

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Speaker 3: I am I cover all sorts of different AI companies

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Speaker 3: and what they're trying to do and what their mission is.

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Speaker 3: And over the last years it's been fascinating because you know,

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Speaker 3: you're talking to folks like who say they want to

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Speaker 3: cure loneliness with AI. And as I was sitting there

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Speaker 3: listening to what y'all were announcing on stage, and just

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Speaker 3: to give a little bit of the things that I'm

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Speaker 3: that I were like, oh I would use this or

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Speaker 3: oh okay, I would probably use this, you know, point

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Speaker 3: your iPhone.

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Speaker 4: At the bill, be able to split the bill.

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Speaker 2: Yeah.

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Speaker 3: Tab organization like tab aholic, like in front of so

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Speaker 3: many tabs open right now.

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Speaker 4: It stresses me out.

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Speaker 3: The notes app I have, like very disorganized notes. I

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Speaker 3: took a lot when you were speaking. But now you're

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Speaker 3: able to use Siri writ click it and the next

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Speaker 3: thing you know, it can organize it and send an email.

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Speaker 3: You can have it scan and look at text messages

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Speaker 3: and you know, get a podcast in that way.

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Speaker 4: Spatial reframe. I mean not I'm not going to announce

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Speaker 4: all the things that.

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Speaker 2: You're doing, right, you don't need to do.

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Speaker 4: An announce all. We're good. But but my point in

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Speaker 4: all of this is like.

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Speaker 3: When I think about this anticipation about what Apple's going

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Speaker 3: to announce, and don't get mad at me for saying this, Okay,

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Speaker 3: it's not sexy.

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Speaker 4: It's well it is to the developers.

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Speaker 3: It's not like sexy like you're going to cure loneliness

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Speaker 3: or like cancer. But it's it's utility some degree, well, yeah,

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Speaker 3: and usefulness.

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Speaker 4: So is that the point of it is.

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Speaker 1: That I think that utility is that the foundation of

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Speaker 1: human creativity and and ultimately time for connection. Right, I

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Speaker 1: mean I think the the the unlock around all of

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Speaker 1: this is that you get to live the rest of

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Speaker 1: your life and you get to feel really empowered doing it.

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Speaker 2: I guess that's where the sexy.

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Speaker 1: Part comes in, right. I don't think the sexy part

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Speaker 1: actually belongs in the computer. It belongs it belongs in

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Speaker 1: your life. And so that's that's our focus. I mean

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Speaker 1: the idea of AI as a solution for for loneliness.

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Speaker 1: I mean, loneliness is about a lack of connection to

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Speaker 1: real people, you know, real human We do think it

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Speaker 1: should be real people, and we think.

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Speaker 3: We're There are no AI girlfriends or boyfriends being created

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Speaker 3: with the updated serri AI.

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Speaker 1: No, no, no, quite quite the opposite, because as you

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Speaker 1: may know, if you use many of the existing chatbots,

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Speaker 1: they're really focused on engagement to a large degree, Like

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Speaker 1: they they end sick of fancy, right, They they kind.

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Speaker 2: Of want to pull you in.

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Speaker 5: Uh.

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Speaker 1: They might encourage you to reveal things about yourself and

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Speaker 1: then use that as a basis to establish a connection,

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Speaker 1: and we view it quite the opposite. I mean, the

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Speaker 1: way that we have designed Siri, Siri really wants to say, listen,

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Speaker 1: that's not what I'm here for, right, I'm here to

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Speaker 1: I'm here to help you. I can help you get

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Speaker 1: things done. I can help you learn about the world.

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Speaker 1: But if you try to engage Siri as a romantic partner,

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Speaker 1: series not that.

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Speaker 2: Yeah, Serius, send not into that. Y.

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Speaker 3: Yeah, that's you know, jos I said, I saw something

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Speaker 3: that you said in an interview about how you almost

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Speaker 3: like sometimes and if I slaughter, you'll tell me, yeah,

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Speaker 3: but you don't want people to even know sometimes it's AI.

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Speaker 6: Or you like it one of my favorites.

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Speaker 3: When they don't realize it's AI, it kind of disappears.

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Speaker 3: So can you paint the picture of what that looks like?

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Speaker 6: Well, what Craig said that goes back a lot to

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Speaker 6: our roots. We like when technology disappears, right, you just

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Speaker 6: focus on what you want to do. You focus on

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Speaker 6: the content. And it's the same thing with AI. Craig

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Speaker 6: said it, and you referenced it. We don't do AI

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Speaker 6: for AI's sake. Hey, look at us, We're doing AI.

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Speaker 6: It's how as AI make everything better, and that makes

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Speaker 6: our products better, our features better, and I love it

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Speaker 6: when AI actually made that feature better, you didn't have

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Speaker 6: to know you were an AI. We don't want our

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Speaker 6: users to have to be prompt experts right to get

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Speaker 6: to get value out of what we're doing in our features.

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Speaker 6: We want to meet them where they're at, have the

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Speaker 6: products and features become better. And this is just a

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Speaker 6: really helpful technology and making those features in products better.

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Speaker 2: Yeah, you mentioned a few of our features and thank

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Speaker 2: you again for doing that.

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Speaker 1: But if you think about something as simple as you

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Speaker 1: receive a text message people are talking about dinner. Someone says,

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Speaker 1: how about this weekend, let's get together at six, and

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Speaker 1: we just drop a little button into the chat transcript

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Speaker 1: that says add to calendar right now. Turned out there

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Speaker 1: had to be a bunch of AI to understand that

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Speaker 1: you were talking about an event, and then when you

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Speaker 1: hit ad the calendar, it figures out looking reading that conversation,

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Speaker 1: it understands, oh, here's where it here's where it is,

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Speaker 1: here's when it is, here's who it's with. And so

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Speaker 1: up comes a little sheet with a filled out calendar event.

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Speaker 5: Well to you.

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Speaker 1: That's just, of course right as a human that seems

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Speaker 1: like the most natural thing in the world. Well, that

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Speaker 1: was a bunch of AI trying to understand something. But

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Speaker 1: you didn't have to think about I'm interacting with AI.

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Speaker 1: You just thought, oh, add to calendar. Good, hooray, move on,

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Speaker 1: you know, to him eliminated.

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Speaker 3: So much of what y'all are talking about with the

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Speaker 3: updated sery comes down to it understands your personal context.

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Speaker 3: Can you explain what that means to folks who might

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Speaker 3: not understand.

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Speaker 1: Yeah, it can be everything from understanding you know who

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Speaker 1: your child is, who your parent is. You'll often want

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Speaker 1: to refer in really natural terms to send this to.

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Speaker 2: Mom or where where where's my kid?

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Speaker 1: And understands who those people are, so it can solve

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Speaker 1: the problem for you in the most natural way. It's

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Speaker 1: also about where are you in the moment?

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Speaker 2: You know.

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Speaker 1: I use Siri now where I'm looking at some information

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Speaker 1: about a show.

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Speaker 2: I see an actor and I wonder where do they

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Speaker 2: grow up?

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Speaker 1: I just literally type where did they grow up? And

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Speaker 1: it knows what I'm looking at at that moment. I'm

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Speaker 1: not typing their name or doing aybody, and it can

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Speaker 1: draw from the context of exactly as if, as if

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Speaker 1: Siri is is there with me, understands what I understand

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Speaker 1: and can take the next step with me.

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Speaker 6: What I love about that too, is to make it

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Speaker 6: clear we don't know that right point your device, your

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Speaker 6: iPhone or your Mac or iPad, and by the way

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Speaker 6: it works across all of them, it knows this right

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Speaker 6: through this incredibly private by design mechanism that does not

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Speaker 6: send this all to something that we become profiling you

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Speaker 6: and creating a monetization opportunity oty. You know, this is

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Speaker 6: very private information. It stays on your device.

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Speaker 1: Yeah, and that's so critical because I think it is

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Speaker 1: a challenging thing for a lot of people to understand

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Speaker 1: the distinction between what your iPhone knows and what say,

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Speaker 1: Apple as a company knows your iPhone is yours, right,

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Speaker 1: your data is yours, and it stays on your phone

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Speaker 1: and your control and Siri is using it for you.

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Speaker 1: Apple doesn't get to know any of this stuff. And

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Speaker 1: that is very different than most players in the space,

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Speaker 1: and I think super important.

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Speaker 3: I would love to get I definitely want to get

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Speaker 3: into privacy. I'd love to get into design decisions. Yeah,

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Speaker 3: it's so interesting. You walk around Apple Park.

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Speaker 4: It's very true. Just for our listeners and viewers.

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Speaker 3: It's very tranquil here, Yes, it is, and you really

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Speaker 3: kind of get the sense the privacy too, right, is

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Speaker 3: almost like there's like compounds that look like genius bars.

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Speaker 4: Everyone. It's crazy, it's really interesting.

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Speaker 3: I was my.

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Speaker 4: Yeah, at my first that was my first time here.

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Speaker 3: But I imagine that the conversations that y'all have behind the

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Speaker 3: closed doors here about design really impact everything because when

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Speaker 3: it comes to the future of AI and you mentioned

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Speaker 3: this a little bit, this idea of.

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Speaker 4: Ending with a question mark.

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Speaker 3: Or these ais ai that is really agreeable. I was

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Speaker 3: joking with Jaws the other day and said that chat

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Speaker 3: GPT recently said to me, mom to mom, and I

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Speaker 3: was like, wow, elln You're not a mom, you know,

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Speaker 3: but I'm sure that with some kind of error. But

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Speaker 3: these design, these design decisions, the decisions you make behind

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Speaker 3: closed doors here at Apple Park can impact all of

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Speaker 3: our lives.

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Speaker 6: Before Craig gives you a meeting answered, let me tell

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Speaker 6: you one of my favorite moments. Yesterday we announced the

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Speaker 6: changing of the curve of the corner of our windows

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Speaker 6: and people cheered, and that's because design is so important

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Speaker 6: to Apple. It is so important to our users, it

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Speaker 6: is so important to our developers. I couldn't imagine another

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Speaker 6: company on the planet that would have a meeting like

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Speaker 6: that and talk about a detail like that which would

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Speaker 6: get cheering from the crowd. That's how important it is

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Speaker 6: to us and our community. So what you're bringing up

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Speaker 6: is year is now.

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Speaker 3: You got to the mediaster to that point, Design when

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Speaker 3: it comes to AI can mean life and death. You know,

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Speaker 3: I spoke to a mother who lost her son after

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Speaker 3: after he became addicted to a character AI Chatbi and

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Speaker 3: so I you know, I'm curious about the conversations. If

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Speaker 3: you could just give us take us to the rooms.

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Speaker 3: I know y'all are very secret. I know you don't

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Speaker 3: say anything, but if you prefer to want to say something,

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Speaker 3: tell us about the design decisions behind the scenes, like

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Speaker 3: what did you decide not to do in order to

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Speaker 3: make safe for human first AI?

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Speaker 1: Well, I think Jaws one part of design, which of

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Speaker 1: course is attention to details. That's a huge part of

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Speaker 1: who Apple is, and we have customers who resonate with

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Speaker 1: that to a degree that they hold us to the

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Speaker 1: highest standard. But the other part of design is rooted

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Speaker 1: in our values, I mean who people are drawn to

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Speaker 1: Apple for specific reasons because of who we are. We

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Speaker 1: grew up, many of us, we grew up with Apple

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Speaker 1: technology in our lives. We were attracted to this place

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Speaker 1: because of the way it resonated. And so there is

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Speaker 1: a common set of values that are beneath everything we do.

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Speaker 1: And we all have families and friends that use these products.

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Speaker 2: We ourselves are huge users of our products. We're not

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Speaker 2: We're not building this for someone else that we don't

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Speaker 2: understand or care about.

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Speaker 1: We're building this first and foremost for people that are

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Speaker 1: the closest people in our lives. And so the design

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Speaker 1: process is all about, well, what would I want to

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Speaker 1: for my for myself and for people I care about

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Speaker 1: to have in the world something that doesn't exist, something

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Speaker 1: that's missing, something that could be made better. And that's

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Speaker 1: where our discussions start in all of these cases, where

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Speaker 1: we're talking about how it should be and what's the

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Speaker 1: what's the right thing that would be better in the world.

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Speaker 2: And there are a lot of we talk about the

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Speaker 2: rock Tumbler at Apple, which is a lot of ideas.

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Speaker 1: The rock Tumbler, I mean, it's a wonderful story that

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Speaker 1: that Steve Jobs told years ago about I was involved

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Speaker 1: in a neighbor and showing them if you put these

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Speaker 1: rough gravel into one of those machines that slowly rotated

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Speaker 1: and all the rocks banged off each other, that after

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Speaker 1: enough time, what came out as an unbelievably beautiful polished stone.

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Speaker 1: And that's to say that a bunch of people come

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Speaker 1: together in this design process with different ideas, different perspectives,

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Speaker 1: and we bang off each other.

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Speaker 2: Right, It's not it's.

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Speaker 1: Not a completely sterile organized process. It's throwing a lot

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Speaker 1: of ideas around, trying them out, respecting everyone's points of view,

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Speaker 1: and ultimately coming out with something better than any one

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Speaker 1: of us could have possibly managed ourselves.

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Speaker 2: I mean, the other element of.

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Speaker 1: This at Apple's design is inherently an iterative process.

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Speaker 2: You have to try things. Something that sounds good in concept.

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Speaker 1: If you just try to rush that straight out to

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Speaker 1: the public, that probably wasn't an actual good idea. You

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Speaker 1: try it out and you realize what's good about it,

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Speaker 1: what needs work on it, And so we all live

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Speaker 1: on our products under development for a long time before

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Speaker 1: the public ever sees them right, and that in that

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Speaker 1: process we immediately discover so much, and we get back

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Speaker 1: together and we say, hey, this is what felt like

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Speaker 1: it worked, and this is what didn't work.

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Speaker 2: And this is something that's missing.

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Speaker 1: And so you talk about a meeting, but it's not

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Speaker 1: just one meeting. It's many, many, many meetings. And I

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Speaker 1: think you'd be surprised at the people.

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Speaker 2: That are in that room. Are you know, most of

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Speaker 2: the executive team at times.

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Speaker 1: I mean, we've moved together from an incredibly diverse set

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Speaker 1: of talents from every level of the organization because there's

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Speaker 1: nothing more important than the substance of how our products work,

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Speaker 1: and everyone at the company cares about it, and so

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Speaker 1: we're we're all deeply involved.

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Speaker 6: It's also worth building on one thing you said earlier.

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Speaker 6: The motivations of Apple are different than some other companies.

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Speaker 6: Craig mentioned it when we how we give you an

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Speaker 6: answer in Siri versus maybe how some other people do it.

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Speaker 6: We're not motivated to keep you engaged and keep you

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Speaker 6: on your device.

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Speaker 2: That we are we.

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Speaker 4: All are already addicted to me.

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Speaker 6: Well that is, that is not what we're trying to do,

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Speaker 6: because that's there's no benefit to us in that right.

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Speaker 6: Some people their whole business model is about I need

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Speaker 6: to keep you in what you're in. I need to

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Speaker 6: keep you in my app, my experience. That's how I

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Speaker 6: make my money. That's not us. So we can truly

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Speaker 6: be built around what is the user need, not how

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Speaker 6: do we keep you engaged? And so that changes the

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Speaker 6: way that the design works. To Craig's point, we can

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Speaker 6: deliver more concisely answer. We don't have to try to

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Speaker 6: encourage you to say, hey, now take it further, take

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Speaker 6: it further, because that isn't thing I give you the answer.

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Speaker 6: You want to go further, you can, but we're not

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Speaker 6: trying to drive you to go further.

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Speaker 2: Right.

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Speaker 4: One of the things before we move on from AI just.

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Speaker 3: In general, that I thought was so fascinating when you

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Speaker 3: talk about meeting people with the problems they have, is uh,

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Speaker 3: now with this update, we're going to get notifications. We've

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Speaker 3: already always gotten notifications from Apple that our passwords are

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Speaker 3: leaked somewhere they need to be changed.

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Speaker 4: But now what you guys.

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Speaker 3: Are actually going to be able to do is go

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Speaker 3: log in and change passwords.

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Speaker 4: I wrote this question. My producer looked at and she's like, wait, what.

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Speaker 3: So I just for the people I need you to

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Speaker 3: explain you're going to make us safer.

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Speaker 4: That's also terrifying, like how does that? How does that work?

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Speaker 3: And it's it's super interesting, especially now that so much

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Speaker 3: of our data has been leaked, so much of our

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Speaker 3: data is out there now.

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Speaker 2: Yeah.

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Speaker 1: Yeah, so for for some time now, our passwords app

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Speaker 1: of course could analyze what passwords you've used, that you've

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Speaker 1: recorded with the passwords app that it knows are weak password.

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Speaker 1: If you have the password you know welcome or password

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Speaker 1: you know, we're going to say, hey, bad choice, But

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Speaker 1: we also know passwords we're exposed in data leaks, the

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Speaker 1: data breaches, and we can flag for you, hey, this

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Speaker 1: password is known to attackers, not necessarily known that you

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Speaker 1: use that password, but they maintain the whole dictionary of

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Speaker 1: all the passwords they've ever seen, and they use them

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Speaker 1: to brute force attack accounts. And so if you're using

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Speaker 1: one of those, that's an insecure password. So it's been

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Speaker 1: great in pointing it out, but of course we all

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Speaker 1: have better things to do than painstakingly go to every site,

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Speaker 1: find a password change and that's a frustrating process, and

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Speaker 1: come up with a new password. But Safari has always

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Speaker 1: known how when you were in the password change field

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Speaker 1: to say, here's a more secure password. I could fill

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Speaker 1: that into these fields and I could save it for

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Speaker 1: you as a replacement for your bad password. Well, now

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Speaker 1: that we have the AI and these this agentic tech,

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Speaker 1: it can actually operate a web page behind the scenes.

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Speaker 2: It can go to the website for.

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Speaker 1: You in the background, sort of running a little version

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Speaker 1: of Safari behind the scenes. Go to that password change

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Speaker 1: screen for you, and or your past password that you

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Speaker 1: had in the password field come up locally on your device.

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Speaker 1: This is going to Apple, but with a password only

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Speaker 1: known to your iPhone, but in the field is the

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Speaker 1: new password. Save it off in the passwords app, and

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Speaker 1: next time you go to the site, Safari is going

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Speaker 1: to auto fill that secure password for you, and no

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Speaker 1: longer are you using that insecure password.

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Speaker 6: It's super cool.

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Speaker 3: I do think, you know, we hear so much from

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Speaker 3: Apple about bringing humanity and that it's making things personal.

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Speaker 3: And I think over in Silicon Valley and it is

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Speaker 3: beautiful here and on campus, and it really feels like

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Speaker 3: you're living in the future to some degree. And then

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Speaker 3: I sometimes step out and you see so many folks

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Speaker 3: who have anxiety about artificial intelligence and jobs, who have

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Speaker 3: the rise of sexually explicit deep fakes in high schools

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Speaker 3: this year. I mean, I don't know if y'all were

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Speaker 3: commencement speakers this year, but good luck if you were,

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Speaker 3: because they're getting booed for anything AI related. What do

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Speaker 3: you say to folks, as folks who kind of sit

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Speaker 3: with a front row seat to the future, what do

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Speaker 3: you say to folks who are worried about AI and

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Speaker 3: its role in our lives as it's as it's going.

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Speaker 1: Yeah, I have kids of roughly that age, spanning those ages,

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Speaker 1: and they're they're all deeply ambivalent about it, you know,

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Speaker 1: And I think I think Americans are very deeply ambivalent

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Speaker 1: about it in ways that interestingly people in China seem

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Speaker 1: to be much much less so. So it's a it's

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Speaker 1: an interesting phenomena right now, but I think it's with

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Speaker 1: with some good reason. I think that AI, in Apple's view,

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Speaker 1: can be used to this incredibly empowering thing, as we

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Speaker 1: talked about early earlier. But there is a sense that,

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Speaker 1: for one, things are changing very fast in ways that

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Speaker 1: I think it's hard for any normal person to keep

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Speaker 1: up with. There's uncertainty about where does this all lead

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Speaker 1: and while I think we can look at this as

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Speaker 1: you know, yet another thing of the scale of the

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Speaker 1: Industrial Revolution, which changed our world in a giant way

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Speaker 1: that displaced a lot of people in the process, and

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Speaker 1: still occurred over like eighty years, and now this is

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Speaker 1: happening in a compressed time frame, and so I think

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Speaker 1: it's fair for people to say, Wow, I'm not quite

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Speaker 1: certain what this is going to mean for me. And

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Speaker 1: if you're a student and you're thinking, did I study

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Speaker 1: the right thing? Is the job that I thought was this?

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Speaker 1: The skill that I thought was going to be useful?

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Speaker 1: Is that the one that's going to be useful now

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Speaker 1: that AI is quickly learning all of these things. I

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Speaker 1: think those are all reasonable thoughts to have. You know,

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Speaker 1: we're we're in California, we're optimists. We're trying to do

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Speaker 1: the right thing where where we can build the right

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Speaker 1: the play play the right role in our sense, and

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Speaker 1: I do think in the end this all has a

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Speaker 1: happy ending. But I can certainly relate to to people

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Speaker 1: who say, wow, this is.

443
00:21:02,119 --> 00:21:02,680
Speaker 2: A big change.

444
00:21:02,680 --> 00:21:05,800
Speaker 1: I mean, honestly, there's no at this moment in time,

445
00:21:05,840 --> 00:21:08,520
Speaker 1: there's no bigger place where there's that change than in

446
00:21:08,560 --> 00:21:11,600
Speaker 1: software engineering. It's literally the first job that AI is

447
00:21:12,200 --> 00:21:14,600
Speaker 1: showing that it can do to an incredible degree, and

448
00:21:14,680 --> 00:21:17,960
Speaker 1: so everyone who works in my organization is saying, Wow,

449
00:21:18,000 --> 00:21:19,400
Speaker 1: this thing does a lot of things that I used

450
00:21:19,400 --> 00:21:21,040
Speaker 1: to take a lot of pride in being, you know,

451
00:21:21,200 --> 00:21:23,960
Speaker 1: spending decades learning to do well, and it already does

452
00:21:23,960 --> 00:21:24,359
Speaker 1: it well.

453
00:21:24,440 --> 00:21:25,840
Speaker 4: What has to be true for there to be a

454
00:21:25,840 --> 00:21:26,480
Speaker 4: happy ending.

455
00:21:27,280 --> 00:21:28,919
Speaker 6: Well for our part, we're doing our part right.

456
00:21:28,960 --> 00:21:29,959
Speaker 5: We're building it around you.

457
00:21:30,000 --> 00:21:32,000
Speaker 6: We're building you know, as Greg talked about earlier, as

458
00:21:32,040 --> 00:21:35,040
Speaker 6: we discussed, we're trying to look at it as a

459
00:21:35,520 --> 00:21:39,280
Speaker 6: tool for you. You know, I've been around long enough that

460
00:21:39,359 --> 00:21:42,680
Speaker 6: I remember personal computer is coming and people having similar anxieties.

461
00:21:42,720 --> 00:21:44,959
Speaker 6: It was the idea, why would I ever need an accountant?

462
00:21:45,440 --> 00:21:47,320
Speaker 6: Now that there's Lotus one, two three, which was the

463
00:21:47,440 --> 00:21:51,719
Speaker 6: predecessor to things like Excel, And the reality is it

464
00:21:51,880 --> 00:21:55,720
Speaker 6: didn't replace accounts. It became a powerful tool for accounts

465
00:21:55,760 --> 00:21:59,040
Speaker 6: that allowed them to do more. And I think a

466
00:21:59,080 --> 00:22:01,800
Speaker 6: lot of computers has been that way over years. To

467
00:22:01,840 --> 00:22:04,760
Speaker 6: Craig's point, this is a lot happening fast, and that

468
00:22:04,920 --> 00:22:09,440
Speaker 6: uncertainty is certainly understandable. That's why again, companies like Apple

469
00:22:09,480 --> 00:22:11,560
Speaker 6: or importantcause we'll try to bring the humanity to these things.

470
00:22:11,720 --> 00:22:26,240
Speaker 5: In what we do.

471
00:22:26,280 --> 00:22:28,080
Speaker 4: We want to talk a little bit about privacy.

472
00:22:28,240 --> 00:22:30,639
Speaker 3: There was talk of rebuilding therea from the ground up,

473
00:22:30,880 --> 00:22:34,920
Speaker 3: and tell me what does privacy look like in an

474
00:22:34,960 --> 00:22:37,240
Speaker 3: AI age where we're told that the more data that

475
00:22:37,280 --> 00:22:39,040
Speaker 3: we give and the more data that we share, the

476
00:22:39,040 --> 00:22:42,480
Speaker 3: more personalized these systems are and the better they are.

477
00:22:42,560 --> 00:22:44,359
Speaker 4: What does that look like from an Apple standpoint?

478
00:22:44,760 --> 00:22:48,200
Speaker 1: Yeah, I think you can separate it into two big pieces.

479
00:22:48,560 --> 00:22:52,080
Speaker 1: One is how these AI systems are trained in the

480
00:22:52,080 --> 00:22:56,679
Speaker 1: first place, how these models are built. And years ago,

481
00:22:56,480 --> 00:22:59,520
Speaker 1: to build a reasonable model for a given task, you

482
00:22:59,560 --> 00:23:04,119
Speaker 1: needed a lot of information exactly targeting that task, and

483
00:23:04,160 --> 00:23:05,840
Speaker 1: a lot of companies took the shortcut of saying the

484
00:23:05,880 --> 00:23:08,480
Speaker 1: quickest way to do that is to gather data from

485
00:23:08,640 --> 00:23:13,560
Speaker 1: real users, their own personal data performing that task. On

486
00:23:13,600 --> 00:23:17,240
Speaker 1: the good news side, these models are now so powerful

487
00:23:18,280 --> 00:23:21,400
Speaker 1: that they've generalized to where they can take on new

488
00:23:21,440 --> 00:23:27,040
Speaker 1: tasks with relatively little new information, and so I think

489
00:23:27,040 --> 00:23:30,680
Speaker 1: it's far less necessary than it had been in the past.

490
00:23:30,720 --> 00:23:33,560
Speaker 1: And Apple is always not we wouldn't take the easy road.

491
00:23:33,560 --> 00:23:36,960
Speaker 1: If we need data to train a new model, we're

492
00:23:36,960 --> 00:23:38,879
Speaker 1: going to license it, or we're going to go create

493
00:23:38,920 --> 00:23:39,560
Speaker 1: it ourselves.

494
00:23:39,560 --> 00:23:40,919
Speaker 2: We're going to find a way to do it in

495
00:23:40,920 --> 00:23:42,640
Speaker 2: a way that never involves.

496
00:23:42,280 --> 00:23:46,119
Speaker 1: Using our customer's private information. That's totally now possible. The

497
00:23:46,160 --> 00:23:48,760
Speaker 1: other thing, though, is given powerful AI. We think the

498
00:23:48,800 --> 00:23:54,119
Speaker 1: most powerful useful AI is personal is if you have

499
00:23:54,119 --> 00:23:56,480
Speaker 1: someone who's doing a job for you. It helps if

500
00:23:56,480 --> 00:23:59,560
Speaker 1: they already understand you and what you care about, and

501
00:23:59,600 --> 00:24:04,520
Speaker 1: what you're relationships are, what you're currently doing, what your

502
00:24:04,560 --> 00:24:07,480
Speaker 1: calendar says, you know what messages you've just received, all

503
00:24:07,520 --> 00:24:11,199
Speaker 1: of those things, and there are some wildly different versions

504
00:24:11,240 --> 00:24:14,080
Speaker 1: of how that's done. Most of the industry says the

505
00:24:14,080 --> 00:24:18,320
Speaker 1: way to do that is to give those companies access

506
00:24:18,359 --> 00:24:20,960
Speaker 1: to all of that personal information where they can read it,

507
00:24:21,000 --> 00:24:23,360
Speaker 1: they can use it for variety of purposes, and then

508
00:24:23,359 --> 00:24:25,480
Speaker 1: that makes it easy for them to feed.

509
00:24:25,200 --> 00:24:27,720
Speaker 2: That to their AI to do what you asked the

510
00:24:27,760 --> 00:24:28,320
Speaker 2: AI to do.

511
00:24:28,920 --> 00:24:31,000
Speaker 1: It also opens the door to all kinds of other

512
00:24:31,040 --> 00:24:35,159
Speaker 1: problems that are security problems, privacy problems, and so forth.

513
00:24:36,000 --> 00:24:39,520
Speaker 1: In our case, we believe that that personal intelligence is

514
00:24:39,560 --> 00:24:42,720
Speaker 1: incredibly important, but you have to architect to make sure

515
00:24:42,920 --> 00:24:46,240
Speaker 1: that only you and your device that you control is

516
00:24:46,280 --> 00:24:48,639
Speaker 1: in possession of that information, and so we've gone to

517
00:24:49,359 --> 00:24:51,840
Speaker 1: great links. I think done some really breakthrough work in

518
00:24:51,920 --> 00:24:54,199
Speaker 1: how we do on device processing and how we've created

519
00:24:54,280 --> 00:24:57,680
Speaker 1: even in the cloud, a system we call private cloud

520
00:24:57,680 --> 00:25:01,040
Speaker 1: compute that extends that same private model and the phone

521
00:25:01,560 --> 00:25:03,960
Speaker 1: to computation in the clouds, so that you can use

522
00:25:04,080 --> 00:25:07,080
Speaker 1: powerful AI without giving your data up, without giving it

523
00:25:07,119 --> 00:25:08,679
Speaker 1: to anyone, including Apple.

524
00:25:09,280 --> 00:25:10,199
Speaker 2: We think that's central.

525
00:25:10,240 --> 00:25:13,240
Speaker 1: We think that's the way AI should be built responsibly.

526
00:25:14,280 --> 00:25:18,920
Speaker 3: I would love to play something for you. Don't worry, no, no, no,

527
00:25:18,960 --> 00:25:19,800
Speaker 3: it's it's okay.

528
00:25:21,480 --> 00:25:24,800
Speaker 4: You know. I recently I read that you love.

529
00:25:24,720 --> 00:25:26,600
Speaker 3: Asking lots of questions, that this is kind of in

530
00:25:26,680 --> 00:25:29,520
Speaker 3: your DNA, and so I.

531
00:25:29,200 --> 00:25:29,919
Speaker 6: Why do you say that?

532
00:25:32,000 --> 00:25:37,240
Speaker 3: I I recently had a scammer call me and they

533
00:25:37,320 --> 00:25:37,840
Speaker 3: don't worry.

534
00:25:37,880 --> 00:25:42,240
Speaker 4: They pretended they were from Google, not Apple. But I

535
00:25:42,280 --> 00:25:44,760
Speaker 4: asked the scammer a question. I said.

536
00:25:44,920 --> 00:25:47,320
Speaker 3: They said his name was Scott Landry. It's not his name,

537
00:25:47,359 --> 00:25:49,880
Speaker 3: but I said to Scott, you know, I.

538
00:25:49,840 --> 00:25:52,720
Speaker 4: Said, what do you have on me? Why do I

539
00:25:52,760 --> 00:25:53,920
Speaker 4: keep getting these calls?

540
00:25:54,200 --> 00:25:55,480
Speaker 3: And I just want to tell you what he said,

541
00:25:55,840 --> 00:25:58,600
Speaker 3: especially as we're entering an era where it's easier and

542
00:25:58,680 --> 00:25:59,880
Speaker 3: easier to get scammed.

543
00:26:00,080 --> 00:26:03,639
Speaker 4: Okay, so this is me and Scott Landry. How do

544
00:26:03,680 --> 00:26:04,719
Speaker 4: you have my info?

545
00:26:04,920 --> 00:26:05,080
Speaker 2: How?

546
00:26:05,480 --> 00:26:06,000
Speaker 4: How are you?

547
00:26:06,040 --> 00:26:08,199
Speaker 3: And why do I keep getting these calls from folks

548
00:26:08,280 --> 00:26:10,480
Speaker 3: like I genuinely don't understand, Like is it just that

549
00:26:10,600 --> 00:26:12,680
Speaker 3: I guess like some my infos on.

550
00:26:12,960 --> 00:26:14,000
Speaker 7: You're on databases?

551
00:26:14,119 --> 00:26:14,600
Speaker 6: Yeah?

552
00:26:15,080 --> 00:26:17,040
Speaker 7: A database? What's about it? Yeah? Do you want me

553
00:26:17,080 --> 00:26:18,680
Speaker 7: to tell you what what I found you from?

554
00:26:18,920 --> 00:26:19,200
Speaker 6: Yeah?

555
00:26:19,240 --> 00:26:22,040
Speaker 7: Sure, what we found you from? So it's a bitcoin sec.

556
00:26:22,160 --> 00:26:23,399
Speaker 7: It's like I don't know what. I don't know what

557
00:26:23,400 --> 00:26:26,520
Speaker 7: there's in relation to you know you know what that is?

558
00:26:26,840 --> 00:26:26,879
Speaker 3: No?

559
00:26:27,400 --> 00:26:29,120
Speaker 7: Yeah, you must have signed up for a bitcoin email,

560
00:26:29,200 --> 00:26:33,240
Speaker 7: bitcoin related email, crypto emails. So like you know those

561
00:26:33,320 --> 00:26:34,320
Speaker 7: databases that get.

562
00:26:34,560 --> 00:26:37,080
Speaker 3: Does it just have like my email or sorry my email?

563
00:26:37,119 --> 00:26:39,240
Speaker 3: My phone number? Like what does it have on it?

564
00:26:39,600 --> 00:26:41,920
Speaker 7: Yeah? So most of thems have email phone number. I've

565
00:26:41,920 --> 00:26:46,080
Speaker 7: had somewhere. I have social right Yeah, so no, you're

566
00:26:46,160 --> 00:26:46,960
Speaker 7: your social is not?

567
00:26:47,480 --> 00:26:47,840
Speaker 5: Yeah?

568
00:26:48,280 --> 00:26:50,680
Speaker 7: I have so I have your Gmail, I have your CNN,

569
00:26:50,720 --> 00:26:53,960
Speaker 7: I have your at turner dot com. Mm hmm, what's

570
00:26:53,960 --> 00:26:54,359
Speaker 7: it called?

571
00:26:54,440 --> 00:26:54,800
Speaker 8: Uh?

572
00:26:55,160 --> 00:26:58,280
Speaker 7: You're expected like you're expected networth or how much you

573
00:26:58,280 --> 00:26:58,480
Speaker 7: make it?

574
00:26:58,560 --> 00:27:03,440
Speaker 3: Your what advising you people to like protect themselves against you.

575
00:27:05,280 --> 00:27:11,080
Speaker 7: It's always evolving, so my my advice won't be won't

576
00:27:11,080 --> 00:27:13,639
Speaker 7: be relevant in a year, in three months. You know,

577
00:27:13,680 --> 00:27:15,920
Speaker 7: the advice I would have given six months ago isn't

578
00:27:15,960 --> 00:27:20,680
Speaker 7: relevant now. There's so many things like, there's so many things.

579
00:27:20,840 --> 00:27:23,200
Speaker 7: I have an I have an operation currently running. It's

580
00:27:23,280 --> 00:27:29,640
Speaker 7: the next wave, which is no, I can't say that.

581
00:27:30,359 --> 00:27:32,639
Speaker 6: Okay, Well, I love the fact, Laurie, you are the

582
00:27:32,680 --> 00:27:35,040
Speaker 6: first person who had a scammer calling it you turned

583
00:27:35,040 --> 00:27:38,240
Speaker 6: into an interview. I absolutely amazing.

584
00:27:39,280 --> 00:27:41,400
Speaker 4: It's good. We do the executives and we also.

585
00:27:41,200 --> 00:27:43,440
Speaker 2: Do the scam We know what you did for a living.

586
00:27:43,520 --> 00:27:45,800
Speaker 2: I mean, if you know a lot about you.

587
00:27:44,680 --> 00:27:48,359
Speaker 4: I did get consent to record him just in case.

588
00:27:48,640 --> 00:27:50,879
Speaker 4: But I guess my question to y'all is, like, you

589
00:27:51,000 --> 00:27:54,480
Speaker 4: listen to this. Our data is everywhere right.

590
00:27:54,560 --> 00:27:57,000
Speaker 3: I know that Apple has always been so focused on privacy,

591
00:27:57,080 --> 00:28:00,800
Speaker 3: so as AI makes everything even more believable, the scams

592
00:28:00,840 --> 00:28:03,399
Speaker 3: are just going to be wild. It took me a

593
00:28:03,440 --> 00:28:06,520
Speaker 3: second to realize Scott Landry wasn't Scott Landry. And you

594
00:28:06,600 --> 00:28:09,000
Speaker 3: talk about the people you love, What advice do you have?

595
00:28:09,200 --> 00:28:12,480
Speaker 3: As the technology gets better and better? It's almost like

596
00:28:12,480 --> 00:28:14,159
Speaker 3: we're in a race to some degree.

597
00:28:14,359 --> 00:28:15,880
Speaker 2: Well, I think that's I think that's right.

598
00:28:16,000 --> 00:28:20,320
Speaker 1: And you know what Scott Landry had it was clearly

599
00:28:20,359 --> 00:28:24,439
Speaker 1: the product of data brokers that as you, if you

600
00:28:24,480 --> 00:28:27,880
Speaker 1: aren't browsing with a secure browser or aren't using apps

601
00:28:27,880 --> 00:28:33,520
Speaker 1: that are respecting your privacy, they are exchanging information between entities,

602
00:28:33,560 --> 00:28:36,680
Speaker 1: They're building a profile, and that profile becomes the things

603
00:28:36,720 --> 00:28:39,640
Speaker 1: that people are trading around and can use for all

604
00:28:39,720 --> 00:28:42,640
Speaker 1: kinds of reasons, often motivated by putting the right ad

605
00:28:42,640 --> 00:28:44,640
Speaker 1: in front of you or marketing something to you, but

606
00:28:44,720 --> 00:28:48,000
Speaker 1: sometimes something far more nefarious than that. And so we

607
00:28:48,120 --> 00:28:53,000
Speaker 1: certainly work to build really great privacy into Safari, great

608
00:28:53,000 --> 00:28:55,720
Speaker 1: things like app tracking, transparency as a standard on the

609
00:28:55,720 --> 00:28:58,840
Speaker 1: app store, so that your information isn't out there. And

610
00:28:59,000 --> 00:29:01,959
Speaker 1: I honestly don't get halls like this because I have

611
00:29:02,000 --> 00:29:05,600
Speaker 1: a very small footprint, because I'm very private about how

612
00:29:06,080 --> 00:29:08,719
Speaker 1: you know, the tools I use and how I browse.

613
00:29:08,760 --> 00:29:11,520
Speaker 1: And so step one is pick pick the right browser,

614
00:29:12,560 --> 00:29:14,160
Speaker 1: pick the right tools, Be.

615
00:29:14,120 --> 00:29:16,320
Speaker 2: Careful where you give your information.

616
00:29:16,960 --> 00:29:17,240
Speaker 5: Uh.

617
00:29:17,280 --> 00:29:21,600
Speaker 1: You know, anytime you fill out a form for some business, uh,

618
00:29:21,680 --> 00:29:25,120
Speaker 1: you often you better trust that business because otherwise they're

619
00:29:25,160 --> 00:29:28,960
Speaker 1: saying they might see monetary value in trading that. But

620
00:29:29,040 --> 00:29:32,800
Speaker 1: I think you raise the next level problem, which is

621
00:29:32,920 --> 00:29:36,080
Speaker 1: where now you'll have not only entities that have all

622
00:29:36,080 --> 00:29:40,000
Speaker 1: this data on you, but can maybe be an AI

623
00:29:40,120 --> 00:29:42,320
Speaker 1: that can fake a voice, you know.

624
00:29:42,320 --> 00:29:43,600
Speaker 2: I mean, they're really bad ones.

625
00:29:43,640 --> 00:29:46,760
Speaker 1: And I've had family members who have fallen prey to

626
00:29:46,920 --> 00:29:51,160
Speaker 1: scams where someone claims to be their grandchild, right and oh,

627
00:29:51,200 --> 00:29:53,680
Speaker 1: I'm in trouble. I need you to bail me out,

628
00:29:53,760 --> 00:29:55,280
Speaker 1: you know, don't call mom and dad. They'll be so

629
00:29:55,360 --> 00:29:57,680
Speaker 1: angry with me. But but you know, Grandpa, can you

630
00:29:57,680 --> 00:30:00,520
Speaker 1: come help bail me out of this situation? And when

631
00:30:00,560 --> 00:30:04,080
Speaker 1: they're pulling on the heartstrings of someone you know in

632
00:30:04,120 --> 00:30:07,480
Speaker 1: that relationship, I think there's parts of our brain that

633
00:30:07,520 --> 00:30:09,920
Speaker 1: maybe aren't you know, because you be vigilant for the

634
00:30:09,960 --> 00:30:12,640
Speaker 1: scam or instead thinking, oh my gosh, I've got a

635
00:30:12,680 --> 00:30:14,720
Speaker 1: family member I care about, how can I go help them?

636
00:30:14,720 --> 00:30:17,120
Speaker 1: And so I think unfortunately people like this are going

637
00:30:17,200 --> 00:30:21,440
Speaker 1: to use every advanced technology they can to prey on people.

638
00:30:21,600 --> 00:30:25,800
Speaker 1: And so learning your digital literacy and learning I mean

639
00:30:25,800 --> 00:30:28,600
Speaker 1: it's sad to say, but learning a degree of skepticism

640
00:30:28,680 --> 00:30:31,000
Speaker 1: toward any contact you are having.

641
00:30:30,800 --> 00:30:34,720
Speaker 2: With any entity that you didn't initiate. Is you know,

642
00:30:34,720 --> 00:30:36,720
Speaker 2: if someone calls up.

643
00:30:36,600 --> 00:30:39,240
Speaker 1: And you you aren't the one to call them, or

644
00:30:39,280 --> 00:30:41,600
Speaker 1: someone sends you an email message and they aren't someone

645
00:30:41,600 --> 00:30:44,120
Speaker 1: you already have contact with. I think you have to

646
00:30:44,240 --> 00:30:47,400
Speaker 1: view that as it potentially this person isn't who they

647
00:30:47,400 --> 00:30:48,080
Speaker 1: say they are.

648
00:30:49,000 --> 00:30:50,080
Speaker 2: Sad state of affairs.

649
00:30:50,080 --> 00:30:52,440
Speaker 6: But I do love the fact, by the way that

650
00:30:52,600 --> 00:30:56,840
Speaker 6: we have worked so hard to try to protect people

651
00:30:56,880 --> 00:30:59,000
Speaker 6: from this. I love the fact that you look at

652
00:30:59,000 --> 00:31:02,240
Speaker 6: Safari on your map, it tells you how many trackers

653
00:31:02,760 --> 00:31:05,160
Speaker 6: it is blocked on your behalf that I didn't didn't

654
00:31:05,200 --> 00:31:08,120
Speaker 6: have to because data brokers are building a profile on you.

655
00:31:08,520 --> 00:31:11,479
Speaker 6: And we've always said, look, we're not against advertising, but

656
00:31:11,520 --> 00:31:15,160
Speaker 6: we want users to have to give consent to their

657
00:31:15,240 --> 00:31:18,520
Speaker 6: information going to somebody else or going to a company

658
00:31:18,680 --> 00:31:21,720
Speaker 6: different than the one that was asking you for that information.

659
00:31:22,160 --> 00:31:23,959
Speaker 6: To us, that has been so important and are going

660
00:31:24,000 --> 00:31:25,680
Speaker 6: It goes back to what we were talking about earlier.

661
00:31:26,080 --> 00:31:29,280
Speaker 6: You know, we're not trying to build You know, Tim

662
00:31:29,320 --> 00:31:33,040
Speaker 6: has said it right that the product's free. It's maybe

663
00:31:33,080 --> 00:31:36,360
Speaker 6: not free, you're the product, right, and that and selling

664
00:31:36,440 --> 00:31:39,200
Speaker 6: the information they gain about you on a free product

665
00:31:39,400 --> 00:31:41,720
Speaker 6: is how they monetize. That's not us, you know. We

666
00:31:41,760 --> 00:31:43,800
Speaker 6: want to try to protect you from that. And Craig

667
00:31:44,240 --> 00:31:46,720
Speaker 6: is too humble to say it. He's been really the spiritual,

668
00:31:47,040 --> 00:31:49,960
Speaker 6: you know, and actual leader and making this happen on

669
00:31:50,040 --> 00:31:50,880
Speaker 6: behalf of users.

670
00:31:51,520 --> 00:31:53,520
Speaker 4: I I'd love I want to play one more.

671
00:31:53,640 --> 00:31:54,200
Speaker 6: Lauren is.

672
00:31:54,960 --> 00:31:55,680
Speaker 4: My name is Lauren.

673
00:31:55,760 --> 00:31:58,480
Speaker 8: She has and I have two kids, one of whom

674
00:31:58,520 --> 00:32:01,080
Speaker 8: is entering middle school and sort of this new phase

675
00:32:01,080 --> 00:32:04,520
Speaker 8: of independent life. We're among a cohort of families that

676
00:32:04,600 --> 00:32:08,800
Speaker 8: wants to delay the smartphone thing for as long as possible.

677
00:32:09,440 --> 00:32:12,360
Speaker 8: We did get her an Apple Watch, but we did

678
00:32:12,360 --> 00:32:17,200
Speaker 8: also find ourselves having to deconstruct the smartphone device experience

679
00:32:17,240 --> 00:32:19,960
Speaker 8: for her. We bought her a digital camera for photos

680
00:32:20,000 --> 00:32:23,080
Speaker 8: and a refurbished iPod for music on the go. It

681
00:32:23,120 --> 00:32:26,840
Speaker 8: doesn't really work. I realize I'm probably in a particular

682
00:32:26,880 --> 00:32:29,320
Speaker 8: bubble here in Brooklyn, but it seems like this trend

683
00:32:29,440 --> 00:32:33,520
Speaker 8: away from smart technology, especially for kids but also adults,

684
00:32:33,760 --> 00:32:37,800
Speaker 8: is really growing. I wonder why Apple, the leader in

685
00:32:37,920 --> 00:32:40,960
Speaker 8: smart technology, doesn't take advantage of this hole in the

686
00:32:41,000 --> 00:32:43,640
Speaker 8: market and create dumb, safe.

687
00:32:43,400 --> 00:32:44,800
Speaker 2: Products for kids.

688
00:32:44,880 --> 00:32:48,760
Speaker 8: In that transitional time period we're an Apple family. But

689
00:32:48,800 --> 00:32:51,080
Speaker 8: if there's another product on the market that allows my

690
00:32:51,160 --> 00:32:54,040
Speaker 8: kid to listen to music, communicate with people I approve,

691
00:32:54,200 --> 00:32:57,400
Speaker 8: take photos, and find her way via GPS, I would

692
00:32:57,480 --> 00:32:57,959
Speaker 8: jump on it.

693
00:32:58,360 --> 00:32:58,680
Speaker 7: Thank you.

694
00:32:58,840 --> 00:33:02,880
Speaker 4: Hey. So will Apple create a dumb phone? Is the question?

695
00:33:03,000 --> 00:33:04,800
Speaker 4: I guess she wanted to know.

696
00:33:05,240 --> 00:33:07,040
Speaker 6: Well, I think there's other questions and better than that.

697
00:33:07,080 --> 00:33:11,440
Speaker 1: But yeah, I think that's a fantastic question, and I

698
00:33:12,440 --> 00:33:15,920
Speaker 1: very much relate to what she is saying. Good news,

699
00:33:16,600 --> 00:33:20,240
Speaker 1: we ship such a product, and it is the iPhone.

700
00:33:20,280 --> 00:33:24,840
Speaker 1: Because what we what we did announce yes yesterday yesterday

701
00:33:25,040 --> 00:33:27,040
Speaker 1: a long week, Yes, it's been a long week yesterday.

702
00:33:27,160 --> 00:33:31,320
Speaker 1: Exactly what we announced yesterday is we want parents to

703
00:33:31,360 --> 00:33:33,760
Speaker 1: be able to start when they set up let's say a.

704
00:33:33,720 --> 00:33:35,320
Speaker 2: New phone that they want to give a child.

705
00:33:36,360 --> 00:33:42,440
Speaker 1: When they set it up, the baseline experience is completely focused.

706
00:33:42,480 --> 00:33:44,320
Speaker 1: It can be focused to the point that what that

707
00:33:44,360 --> 00:33:47,560
Speaker 1: phone does is lets them call mom and dad and

708
00:33:47,720 --> 00:33:51,360
Speaker 1: grandma and grandpa, and that's it. You know, Maybe has

709
00:33:51,400 --> 00:33:53,720
Speaker 1: fine my enabled so the parent parent wants to know

710
00:33:53,800 --> 00:33:56,800
Speaker 1: where they are. Maybe you've enabled the books app or

711
00:33:56,840 --> 00:33:59,880
Speaker 1: the notes app, your choice, but it starts. We viewed

712
00:34:00,160 --> 00:34:04,440
Speaker 1: starting from the simplest phone, the most the most basic

713
00:34:04,800 --> 00:34:08,759
Speaker 1: and simple experience, and then let the parent decide what

714
00:34:08,880 --> 00:34:12,040
Speaker 1: the time is that's right for their child to open

715
00:34:12,160 --> 00:34:16,280
Speaker 1: up the set of capabilities, because I think today parents

716
00:34:16,320 --> 00:34:18,399
Speaker 1: feel sometimes well, gosh, you give the kid the phone

717
00:34:18,400 --> 00:34:21,080
Speaker 1: and suddenly just like throwing them out in the big

718
00:34:21,120 --> 00:34:24,640
Speaker 1: wide world, and you know everything's going to come rushing in.

719
00:34:25,000 --> 00:34:30,320
Speaker 1: And we've really shifted the orientation of our child setup

720
00:34:30,800 --> 00:34:34,359
Speaker 1: to be start focused and make it really easy and

721
00:34:34,440 --> 00:34:37,160
Speaker 1: incremental for the parent to make the right judgment for

722
00:34:37,320 --> 00:34:41,480
Speaker 1: the development of their child and their family's beliefs over time.

723
00:34:41,719 --> 00:34:44,200
Speaker 2: And I think that's a very healthy way to go.

724
00:34:44,520 --> 00:34:46,879
Speaker 3: There was I was it was interesting to be here

725
00:34:46,880 --> 00:34:50,000
Speaker 3: for that keynote because there was a lot of emphasis

726
00:34:50,080 --> 00:34:51,360
Speaker 3: on child safety.

727
00:34:51,520 --> 00:34:52,399
Speaker 4: This was kind of the first.

728
00:34:52,440 --> 00:34:55,440
Speaker 3: It was really you know, a kind of an overhaul

729
00:34:55,560 --> 00:34:57,680
Speaker 3: of quite a bit and doing quite a bit more,

730
00:34:58,320 --> 00:35:00,279
Speaker 3: which I think will be interesting and I'll be very

731
00:35:00,280 --> 00:35:02,160
Speaker 3: curious to see because I remember the first when I

732
00:35:02,200 --> 00:35:05,600
Speaker 3: interviewed Tim Cook years ago as the launch of screen Time. Yeah,

733
00:35:05,760 --> 00:35:08,560
Speaker 3: I blew through those now you know, you guys have

734
00:35:08,600 --> 00:35:10,400
Speaker 3: to do a lot to stop me from using my phone,

735
00:35:10,400 --> 00:35:12,160
Speaker 3: and it did not stop me. So it seems as

736
00:35:12,160 --> 00:35:14,239
Speaker 3: though you've learned a lot over the years of how

737
00:35:14,280 --> 00:35:16,719
Speaker 3: you can actually build not a one size fits all

738
00:35:16,800 --> 00:35:20,840
Speaker 3: model for people, but you know something that different parents

739
00:35:20,880 --> 00:35:23,200
Speaker 3: can use, depending on their child, depending on the age,

740
00:35:23,239 --> 00:35:24,360
Speaker 3: depending on the category.

741
00:35:24,520 --> 00:35:25,160
Speaker 2: That's right.

742
00:35:25,200 --> 00:35:29,239
Speaker 1: I mean it's first, it's so important that the parent

743
00:35:29,320 --> 00:35:32,439
Speaker 1: and the family is the center of because each each

744
00:35:32,520 --> 00:35:34,279
Speaker 1: family is going to be different in this regard. But

745
00:35:34,360 --> 00:35:36,280
Speaker 1: the other emphasis this year is to make it really

746
00:35:36,320 --> 00:35:40,000
Speaker 1: easy and natural for parents because we had a lot

747
00:35:40,080 --> 00:35:42,440
Speaker 1: we've had over time, a lot of different tools out there,

748
00:35:42,440 --> 00:35:44,080
Speaker 1: and in fact, when we go out and explain them

749
00:35:44,120 --> 00:35:46,120
Speaker 1: to people, often they're like, oh my gosh, I didn't

750
00:35:46,120 --> 00:35:48,240
Speaker 1: actually know that existed on the phone.

751
00:35:48,600 --> 00:35:50,080
Speaker 2: Well that's good and bad.

752
00:35:50,120 --> 00:35:52,200
Speaker 1: I mean, our job is partly to make sure that

753
00:35:52,840 --> 00:35:55,040
Speaker 1: you didn't have to go and dig in the forums

754
00:35:55,040 --> 00:35:57,080
Speaker 1: to figure out what you could do to piece together

755
00:35:57,120 --> 00:35:59,799
Speaker 1: a solution for your child. And so now we've tried

756
00:35:59,840 --> 00:36:02,000
Speaker 1: to make it as easy as possible to get to

757
00:36:02,040 --> 00:36:04,200
Speaker 1: that easy starting point with your child and an easy

758
00:36:04,239 --> 00:36:07,680
Speaker 1: as possible to grow in at the rate that makes

759
00:36:07,680 --> 00:36:08,440
Speaker 1: sense for the parent.

760
00:36:22,239 --> 00:36:28,480
Speaker 4: Okay, Jaws, So here's the thing. It's your fortieth anniversary.

761
00:36:28,840 --> 00:36:30,160
Speaker 6: God, you do your homework, don't you know?

762
00:36:30,320 --> 00:36:33,600
Speaker 3: That's pretty extraordinary. I mean, and I'm going to ask

763
00:36:33,640 --> 00:36:36,239
Speaker 3: you an impossible question, but I hope that you can

764
00:36:36,280 --> 00:36:38,319
Speaker 3: make it possible by answering this question. One of my

765
00:36:38,320 --> 00:36:44,400
Speaker 3: favorite quotes is Flannery O'Connor quote. A story is a

766
00:36:44,440 --> 00:36:46,399
Speaker 3: way to say something that can't be said in any

767
00:36:46,440 --> 00:36:48,720
Speaker 3: other way. And it takes every word of that story

768
00:36:48,760 --> 00:36:50,719
Speaker 3: to say what the meaning is. It's really hard to

769
00:36:50,760 --> 00:36:54,080
Speaker 3: extract a theme. This is what Clernie O'Connor is saying.

770
00:36:54,120 --> 00:36:58,239
Speaker 3: So Jaws, I'm going to ask you, in honor of

771
00:36:58,280 --> 00:37:00,840
Speaker 3: your fortieth anniversary at Apple, I would love for you

772
00:37:00,880 --> 00:37:03,839
Speaker 3: to try to extract a theme from your story here.

773
00:37:04,600 --> 00:37:08,960
Speaker 6: Wow, Look, I went to Michigan. I know you went

774
00:37:09,000 --> 00:37:13,799
Speaker 6: to Michigan. I hired right out of college. You know,

775
00:37:13,840 --> 00:37:15,880
Speaker 6: we don't look back a lot. You know, it's just

776
00:37:16,000 --> 00:37:18,319
Speaker 6: not the Apple way. We don't spend a lot of

777
00:37:18,320 --> 00:37:21,000
Speaker 6: time being nostalgic. That was something that Steve had kind

778
00:37:21,040 --> 00:37:23,400
Speaker 6: of you know, I thought taught all of us is

779
00:37:23,400 --> 00:37:27,600
Speaker 6: that this industry we're in is a forward looking industry,

780
00:37:27,719 --> 00:37:30,480
Speaker 6: not a backward looking one. But we recently celebrated the

781
00:37:30,520 --> 00:37:34,560
Speaker 6: fiftieth anniversary of Apple a rare time of looking back.

782
00:37:34,800 --> 00:37:37,680
Speaker 6: I'm celebrating my forty, so a rare time of looking back.

783
00:37:39,800 --> 00:37:43,520
Speaker 6: It's weird to feel nostalgic, quite honestly. But my biggest

784
00:37:43,560 --> 00:37:46,440
Speaker 6: thing is just that Apple has always been. Is Craig

785
00:37:46,480 --> 00:37:52,600
Speaker 6: talk about making complex things simple, making it personal, and

786
00:37:52,680 --> 00:37:56,319
Speaker 6: that comes because we have just incredibly amazing people that

787
00:37:58,160 --> 00:38:01,759
Speaker 6: I just feel incredibly appreciative of the people that we

788
00:38:01,840 --> 00:38:07,799
Speaker 6: work with because we share this common thought about doing that.

789
00:38:08,239 --> 00:38:13,120
Speaker 6: You know, it's just amazing how much we jibe together. Right,

790
00:38:13,280 --> 00:38:16,399
Speaker 6: It's you've probably heard me say, it's not about being right,

791
00:38:16,440 --> 00:38:18,760
Speaker 6: it's about doing the right thing. So that rock tumber

792
00:38:19,640 --> 00:38:23,399
Speaker 6: mentality only works if you're willing to change your mind, right,

793
00:38:23,440 --> 00:38:25,600
Speaker 6: It only works if you're willing to engage and say

794
00:38:25,640 --> 00:38:29,080
Speaker 6: that we're willing to listen to each other and then say, okay, yeah,

795
00:38:29,120 --> 00:38:31,240
Speaker 6: that way is better than any one of us thought,

796
00:38:31,360 --> 00:38:35,320
Speaker 6: let's go do it. And I just feel like I

797
00:38:35,360 --> 00:38:38,200
Speaker 6: couldn't imagine being having spent my career anywhere else. Clearly

798
00:38:38,239 --> 00:38:40,520
Speaker 6: I couldn't imagine it because here I am. But I

799
00:38:40,520 --> 00:38:42,960
Speaker 6: couldn't imagine it because this is just such an incredibly

800
00:38:43,000 --> 00:38:47,120
Speaker 6: special place that does such incredibly special things for the world,

801
00:38:47,719 --> 00:38:51,080
Speaker 6: and I just feel incredibly blessed to be here. And

802
00:38:51,120 --> 00:38:53,400
Speaker 6: it's the people. It's the people I work with. It's Craig,

803
00:38:53,480 --> 00:38:57,680
Speaker 6: it's Turnus, it's Johnny, it's the tim It's the people

804
00:38:57,719 --> 00:39:00,000
Speaker 6: that we engage with every day that had this idea,

805
00:39:00,000 --> 00:39:02,560
Speaker 6: idea of let's create the best possible products for the

806
00:39:02,560 --> 00:39:06,480
Speaker 6: best possible experience in the world, damn everything else, you know,

807
00:39:06,760 --> 00:39:09,400
Speaker 6: and it's I don't know, is that a theme, Laurie,

808
00:39:09,520 --> 00:39:10,400
Speaker 6: I think someone.

809
00:39:10,200 --> 00:39:12,439
Speaker 4: Well, I guess the theme is people. If I could

810
00:39:12,440 --> 00:39:12,920
Speaker 4: extract it.

811
00:39:12,920 --> 00:39:15,640
Speaker 3: And I think, as someone who's spent the last forty

812
00:39:15,719 --> 00:39:19,719
Speaker 3: years building products that so many people use, what have

813
00:39:19,760 --> 00:39:20,880
Speaker 3: you learned about people?

814
00:39:22,960 --> 00:39:26,160
Speaker 6: You better have the idea that it is about the product.

815
00:39:26,520 --> 00:39:28,480
Speaker 6: You know, when Apple was failing, you know, I do

816
00:39:28,520 --> 00:39:30,920
Speaker 6: tell people, Look, I joined in eighty six, but what

817
00:39:31,000 --> 00:39:33,479
Speaker 6: happened before ninety seven kind of doesn't count, right, because

818
00:39:33,520 --> 00:39:37,440
Speaker 6: ninety seven is when Steve came back and the company

819
00:39:37,560 --> 00:39:43,080
Speaker 6: was literally on the brink of bankruptcy. And Steve came

820
00:39:43,120 --> 00:39:48,080
Speaker 6: back with the idea that, look, great companies fail because

821
00:39:48,080 --> 00:39:51,720
Speaker 6: they forget about creating great products and we are going

822
00:39:51,800 --> 00:39:56,080
Speaker 6: to make everything we do about the product. And if

823
00:39:56,120 --> 00:39:59,439
Speaker 6: we create great products and we can tell people why

824
00:39:59,440 --> 00:40:02,120
Speaker 6: we think they're great and be a good job of

825
00:40:02,160 --> 00:40:05,400
Speaker 6: both of those, everything else will work out. And it

826
00:40:05,480 --> 00:40:09,040
Speaker 6: is turning out to be pretty prophetic, right because that

827
00:40:09,280 --> 00:40:11,600
Speaker 6: was exactly what we put ourselves to. So we want

828
00:40:11,640 --> 00:40:13,720
Speaker 6: to have people here that are all about the product,

829
00:40:13,880 --> 00:40:17,279
Speaker 6: not about themselves. You know, it's about the product, it's

830
00:40:17,280 --> 00:40:20,799
Speaker 6: about the user, and Tim always talks about it. Our

831
00:40:21,080 --> 00:40:24,920
Speaker 6: north star is, you know, enriching the lives of our users.

832
00:40:25,040 --> 00:40:28,719
Speaker 6: And that's literally the conversations we have. What's the right

833
00:40:28,760 --> 00:40:31,000
Speaker 6: thing to do, what's the right thing to do for

834
00:40:31,080 --> 00:40:34,399
Speaker 6: the user? And man, that's pretty cool.

835
00:40:34,760 --> 00:40:38,239
Speaker 4: I didn't want to bring this up, but I'm going to.

836
00:40:39,840 --> 00:40:43,200
Speaker 3: So the year, I don't know, the year you're ten

837
00:40:43,280 --> 00:40:46,839
Speaker 3: years old, your mom signs you up for computer class.

838
00:40:47,080 --> 00:40:49,920
Speaker 2: Oh wow, And now it feels a lot more to.

839
00:40:49,880 --> 00:40:56,320
Speaker 3: Say this, But apparently you, Craig, leader of Apple, believed

840
00:40:56,360 --> 00:41:00,759
Speaker 3: that computers were proposers. Ah, I think I don't do

841
00:41:00,880 --> 00:41:04,280
Speaker 3: my Yeah, you know things about Craig, I don't go deep.

842
00:41:05,040 --> 00:41:08,560
Speaker 4: So take me to ten year old Craig. I know

843
00:41:08,640 --> 00:41:09,840
Speaker 4: you wanted to be doctor j.

844
00:41:11,080 --> 00:41:11,719
Speaker 2: This is true too.

845
00:41:12,640 --> 00:41:18,600
Speaker 3: It was your idling a lot heavy metal, right, Yeah,

846
00:41:18,800 --> 00:41:19,560
Speaker 3: I've got to make sure.

847
00:41:19,640 --> 00:41:20,480
Speaker 6: Craig was very long.

848
00:41:20,760 --> 00:41:23,640
Speaker 3: By the way, what was it about computers that you

849
00:41:23,680 --> 00:41:26,839
Speaker 3: fell in love with since you were so skeptical.

850
00:41:27,520 --> 00:41:30,239
Speaker 1: It, Well, it was a crazy I mean honestly, it

851
00:41:30,280 --> 00:41:33,000
Speaker 1: was a crazy moment. There was an after school class

852
00:41:33,680 --> 00:41:35,000
Speaker 1: and my mom heard about it.

853
00:41:35,080 --> 00:41:36,719
Speaker 2: She's like, oh, you should take the computer class. I

854
00:41:36,760 --> 00:41:38,360
Speaker 2: literally thought like, oh, the kids are doing that.

855
00:41:38,400 --> 00:41:42,560
Speaker 1: They just want to look cool, you know, Yeah, that'd

856
00:41:42,600 --> 00:41:43,240
Speaker 1: be very different.

857
00:41:43,280 --> 00:41:45,439
Speaker 6: Only in California could you be trying to look cool

858
00:41:45,480 --> 00:41:46,160
Speaker 6: by being a nerd?

859
00:41:47,920 --> 00:41:51,960
Speaker 1: So they build our the library by elementary school had

860
00:41:52,360 --> 00:41:57,040
Speaker 1: you know, a dozen Apple tudes, and we filed in there,

861
00:41:57,120 --> 00:41:58,160
Speaker 1: you know, and they.

862
00:41:58,719 --> 00:42:02,040
Speaker 2: Typing on this thing. And there was this moment.

863
00:42:02,120 --> 00:42:05,000
Speaker 1: I mean, I still remember the program that we wrote,

864
00:42:05,040 --> 00:42:07,000
Speaker 1: which was like, you know, print.

865
00:42:07,160 --> 00:42:08,160
Speaker 2: How old are you?

866
00:42:08,160 --> 00:42:11,680
Speaker 1: You know, input A and like in ten years you

867
00:42:11,719 --> 00:42:13,120
Speaker 1: will be a plus ten.

868
00:42:13,400 --> 00:42:17,120
Speaker 2: I ran that thing and my head exploded, like.

869
00:42:17,239 --> 00:42:20,400
Speaker 1: Every neuron was like, oh my god, the possibilities. My

870
00:42:20,480 --> 00:42:22,959
Speaker 1: mom couldn't about twenty can do twenty or twenty?

871
00:42:22,960 --> 00:42:23,480
Speaker 3: Could I hear you?

872
00:42:23,960 --> 00:42:27,400
Speaker 2: I thought the possibilities are limit less. Any number you

873
00:42:27,400 --> 00:42:30,719
Speaker 2: can put any number in here. It was it just.

874
00:42:30,640 --> 00:42:33,520
Speaker 1: Blew me away, and I couldn't stop thinking about it.

875
00:42:33,560 --> 00:42:35,880
Speaker 1: I couldn't stop talking about it. I started doing all

876
00:42:35,920 --> 00:42:40,200
Speaker 1: these chores and weeding and you know, household like vacuumine

877
00:42:40,200 --> 00:42:41,959
Speaker 1: and all this to earn like another couple of bucks.

878
00:42:41,960 --> 00:42:45,000
Speaker 1: So eventually I could buy my own computer. And I

879
00:42:45,600 --> 00:42:47,960
Speaker 1: honestly just never looked back. I don't know what was

880
00:42:48,000 --> 00:42:50,120
Speaker 1: wrong with me that made that be the one little

881
00:42:50,120 --> 00:42:52,279
Speaker 1: piece that you know, just made the world make sense,

882
00:42:53,080 --> 00:42:56,000
Speaker 1: But it really did. And I, if I reflect on it,

883
00:42:56,840 --> 00:42:58,800
Speaker 1: I think, you know, you live in this world of

884
00:42:59,160 --> 00:43:03,400
Speaker 1: like marac things of cars and airplanes and objects, and

885
00:43:03,440 --> 00:43:05,719
Speaker 1: you wonder how they're all built. And I think I

886
00:43:05,800 --> 00:43:09,440
Speaker 1: felt when I first programmed a computer that I can

887
00:43:09,520 --> 00:43:12,640
Speaker 1: make something happen, That I that I could build something

888
00:43:13,400 --> 00:43:16,560
Speaker 1: that that was suddenly within within reach, and that it

889
00:43:16,640 --> 00:43:19,360
Speaker 1: was kind of like the the more I learned, the

890
00:43:19,680 --> 00:43:22,520
Speaker 1: more I could do. And it was it was interactive.

891
00:43:22,920 --> 00:43:25,920
Speaker 1: It was there was that sense of of uh, you know,

892
00:43:25,960 --> 00:43:28,839
Speaker 1: immediate kind of feedback loop of gratification.

893
00:43:29,520 --> 00:43:29,600
Speaker 5: Uh.

894
00:43:29,719 --> 00:43:32,799
Speaker 1: And once I got on that that in that loop, uh,

895
00:43:32,960 --> 00:43:35,920
Speaker 1: it never let me go, you know, and I feel

896
00:43:36,000 --> 00:43:37,960
Speaker 1: unbelievably blessed for it.

897
00:43:38,080 --> 00:43:40,279
Speaker 2: I mean, I how could how could you not growing.

898
00:43:40,080 --> 00:43:42,279
Speaker 1: Up in California happen to be just down the road,

899
00:43:42,360 --> 00:43:45,000
Speaker 1: you know, from fundamentally from all of this happening, and

900
00:43:45,040 --> 00:43:48,520
Speaker 1: getting just exposed it at the right moment and falling

901
00:43:48,560 --> 00:43:49,120
Speaker 1: in love with it.

902
00:43:49,640 --> 00:43:51,600
Speaker 6: Either way, I will tell you, I know that Craig

903
00:43:51,680 --> 00:43:55,040
Speaker 6: is a good friend. And even though he's the cheap

904
00:43:55,200 --> 00:43:58,200
Speaker 6: of all the software engineering here, as you said, he

905
00:43:58,239 --> 00:43:59,280
Speaker 6: still loves the code.

906
00:43:59,440 --> 00:44:04,600
Speaker 4: You know, he's everything. What happened to your hobby?

907
00:44:04,920 --> 00:44:06,680
Speaker 2: Yeah, I mean it's I do.

908
00:44:06,880 --> 00:44:11,320
Speaker 1: It's It's been my habit on vacation often over Thanksgiving,

909
00:44:11,320 --> 00:44:14,200
Speaker 1: a Christmas or so forth, that that those are those

910
00:44:14,200 --> 00:44:17,200
Speaker 1: are coding vacations. That's where I get to go build

911
00:44:17,280 --> 00:44:21,400
Speaker 1: these hobby projects and over you know, the last decade,

912
00:44:21,480 --> 00:44:23,400
Speaker 1: that's I've been doing it the old fashioned way, you know,

913
00:44:23,520 --> 00:44:26,480
Speaker 1: using Often after WWDC we announce a whole bunch of

914
00:44:26,480 --> 00:44:28,640
Speaker 1: APIs and new language features, and so I go kick

915
00:44:28,680 --> 00:44:30,239
Speaker 1: the tires on all of those and have a lot

916
00:44:30,239 --> 00:44:33,359
Speaker 1: of fun. And now it's a I And honestly, over

917
00:44:33,400 --> 00:44:36,719
Speaker 1: the last year, I've just been that much more ambitious,

918
00:44:36,920 --> 00:44:40,560
Speaker 1: you know. It's I think there's a sense that like

919
00:44:40,680 --> 00:44:43,560
Speaker 1: if you if you were someone who was an interior

920
00:44:43,600 --> 00:44:46,040
Speaker 1: designer and in the past, you know, you had to

921
00:44:46,239 --> 00:44:48,520
Speaker 1: pound the nail on every little bit of the cabinet

922
00:44:48,520 --> 00:44:50,839
Speaker 1: that you were building, and there was part of that

923
00:44:50,880 --> 00:44:52,640
Speaker 1: you could take some pride that you you knew how

924
00:44:52,680 --> 00:44:53,680
Speaker 1: to do that really.

925
00:44:53,440 --> 00:44:55,239
Speaker 2: Well and you could get that joint just right.

926
00:44:56,160 --> 00:44:58,880
Speaker 1: But you know how ambitious a remodel could you do

927
00:44:58,960 --> 00:45:00,440
Speaker 1: if that's how you were going to do. And now

928
00:45:00,440 --> 00:45:02,080
Speaker 1: you have ai to do a lot of that, and

929
00:45:02,120 --> 00:45:04,000
Speaker 1: you can think bigger about the big picture of the

930
00:45:04,040 --> 00:45:06,319
Speaker 1: design you're creating. You can try more things out and

931
00:45:06,360 --> 00:45:09,040
Speaker 1: so right now, while while a lot of us in

932
00:45:09,040 --> 00:45:11,359
Speaker 1: the field are partly like wow, what does this all

933
00:45:11,400 --> 00:45:14,760
Speaker 1: mean to us, there's a tremendous sense of excitement about

934
00:45:14,800 --> 00:45:16,360
Speaker 1: how much more.

935
00:45:16,160 --> 00:45:19,000
Speaker 2: We can imagine and explore and build.

936
00:45:19,920 --> 00:45:21,879
Speaker 3: I have to wrap it soon, but I wanted to say,

937
00:45:21,960 --> 00:45:23,960
Speaker 3: when I got into tech and covering tech, it was

938
00:45:24,040 --> 00:45:26,600
Speaker 3: like two thousand and nine, so I mean, I haven't

939
00:45:26,640 --> 00:45:29,440
Speaker 3: been if you say, as long as y'all, but it

940
00:45:29,480 --> 00:45:31,239
Speaker 3: felt really punk rock. I was one of the first

941
00:45:31,239 --> 00:45:34,960
Speaker 3: to get an iPhone in college, people thought I was crazy.

942
00:45:35,560 --> 00:45:37,840
Speaker 3: And there was this moment because it wasn't cool to

943
00:45:37,840 --> 00:45:40,120
Speaker 3: go to Wall Street anymore because we had the recession.

944
00:45:40,200 --> 00:45:42,879
Speaker 3: Everything was imploding. But now you could have the app

945
00:45:42,880 --> 00:45:44,520
Speaker 3: store had launched, the iPhone had come out. Now you

946
00:45:44,520 --> 00:45:45,759
Speaker 3: could have an idea and you could code it into

947
00:45:45,760 --> 00:45:47,960
Speaker 3: the hands of millions of people. It was such an

948
00:45:48,000 --> 00:45:50,440
Speaker 3: extraordinary time and there was so much creativity, and there

949
00:45:50,480 --> 00:45:52,200
Speaker 3: was lots of failure, but the stakes.

950
00:45:51,880 --> 00:45:52,920
Speaker 4: Didn't feel as high.

951
00:45:53,560 --> 00:45:56,160
Speaker 3: Now I sit across from tech founders, and the stakes

952
00:45:56,160 --> 00:45:59,400
Speaker 3: feel really really high. And I think about, you know,

953
00:45:59,440 --> 00:46:02,879
Speaker 3: looking at the Apple garage days and these moments where

954
00:46:03,040 --> 00:46:05,160
Speaker 3: just creativity was bursting everywhere.

955
00:46:05,160 --> 00:46:07,680
Speaker 4: And the Apple quote of like, you know, think different.

956
00:46:08,320 --> 00:46:10,880
Speaker 3: How do you think different once you've become the norm,

957
00:46:10,960 --> 00:46:13,600
Speaker 3: once you've become the mainstam, once you're not punk rock anymore?

958
00:46:13,600 --> 00:46:14,960
Speaker 4: And I can say that to you because I know

959
00:46:15,000 --> 00:46:16,080
Speaker 4: that you liked metal.

960
00:46:15,920 --> 00:46:20,319
Speaker 2: And rock, well, I think it is.

961
00:46:20,480 --> 00:46:22,520
Speaker 1: I mean, look that no one, I think is more

962
00:46:22,680 --> 00:46:26,759
Speaker 1: surprised than we are that to go from being the

963
00:46:26,880 --> 00:46:30,600
Speaker 1: underdog to suddenly find like, what what the heck just happened?

964
00:46:31,480 --> 00:46:35,239
Speaker 1: We're kind of successful. That's weird. It doesn't fit with

965
00:46:35,280 --> 00:46:37,719
Speaker 1: your self conception. And you know, Jaws tot he's been

966
00:46:37,760 --> 00:46:41,280
Speaker 1: here forty years. But you look around, Apple is unusual

967
00:46:41,280 --> 00:46:45,560
Speaker 1: and having so many people here that have been here

968
00:46:45,600 --> 00:46:48,880
Speaker 1: for so long and who joined this company not because

969
00:46:48,880 --> 00:46:52,239
Speaker 1: they thought here's here's a rocket ship for you know,

970
00:46:52,600 --> 00:46:57,800
Speaker 1: getting big and financial success, but because they like building

971
00:46:57,840 --> 00:46:58,279
Speaker 1: these things.

972
00:46:58,280 --> 00:46:59,520
Speaker 2: They like doing what Apple did.

973
00:46:59,560 --> 00:47:01,800
Speaker 1: And the people that are still the heart and soul

974
00:47:01,880 --> 00:47:05,000
Speaker 1: of this company and attracted other like minded people. And

975
00:47:05,080 --> 00:47:09,480
Speaker 1: so we're still those people, you know, and now we

976
00:47:09,480 --> 00:47:13,160
Speaker 1: we do get to do harder things. You know, we

977
00:47:13,280 --> 00:47:17,600
Speaker 1: have the resources to you still have to choose, you know,

978
00:47:17,640 --> 00:47:20,719
Speaker 1: we we Jaws And I get the letters that say, like, hey,

979
00:47:20,880 --> 00:47:22,560
Speaker 1: I guess it's emails generally.

980
00:47:22,280 --> 00:47:24,960
Speaker 2: On occasionally on paper. It's weird when that happens.

981
00:47:26,040 --> 00:47:28,319
Speaker 1: You don't say, hey, Apple, you're so successful, why don't

982
00:47:28,360 --> 00:47:31,960
Speaker 1: you do everything? And it turns out you have to

983
00:47:32,160 --> 00:47:34,480
Speaker 1: pick a few things because even as much as as

984
00:47:34,520 --> 00:47:38,680
Speaker 1: we have all this capability, doing things right takes focus.

985
00:47:39,160 --> 00:47:42,120
Speaker 1: But we have the opportunity Apple to do bigger things right.

986
00:47:42,320 --> 00:47:48,200
Speaker 1: And uh, that's still creative and it's still exciting, and

987
00:47:48,280 --> 00:47:50,880
Speaker 1: I think more than ever it makes a big difference

988
00:47:50,880 --> 00:47:53,720
Speaker 1: in the world, and having this opportunity to have that big,

989
00:47:53,800 --> 00:48:00,000
Speaker 1: a hopefully really positive role in people's lives, that's incredibly gratifying.

990
00:48:00,239 --> 00:48:02,719
Speaker 6: Yeah, I it is interesting because I do take and

991
00:48:02,800 --> 00:48:04,839
Speaker 6: it is occasional letter to your point and I hate

992
00:48:04,840 --> 00:48:07,400
Speaker 6: that rather an email. But they got a lot of

993
00:48:07,400 --> 00:48:10,480
Speaker 6: emails too about all the things that Apple should do.

994
00:48:11,080 --> 00:48:14,319
Speaker 6: And usually it's so flattering because it's almost anything that's

995
00:48:14,400 --> 00:48:17,280
Speaker 6: hard or not great in the world, it's like, Apple,

996
00:48:17,320 --> 00:48:20,120
Speaker 6: will you please do it? And it's that it's that

997
00:48:20,880 --> 00:48:23,319
Speaker 6: affirmation that you guys will know how to do this,

998
00:48:23,480 --> 00:48:26,080
Speaker 6: you know how to make it people per first and

999
00:48:26,200 --> 00:48:28,400
Speaker 6: personal and easy to use. And I take that as

1000
00:48:28,440 --> 00:48:31,239
Speaker 6: such a such a compliment when I ask us to

1001
00:48:31,280 --> 00:48:31,960
Speaker 6: do those things.

1002
00:48:31,960 --> 00:48:33,399
Speaker 4: Well, thank you guys so much.

1003
00:48:33,440 --> 00:48:36,520
Speaker 2: Appreciate enjoyed it.