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Speaker 1: Everybody wants to talk to you here because you've got

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Speaker 1: a lot of money. You've got over one hundred million

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Speaker 1: dollars of cash to invest, so people want to see you.

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Speaker 1: Why do you come to Davos because people are just

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Speaker 1: going to be bombarding you give me money for this

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Speaker 1: or that? Is it really worth the Affrica slept all

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Speaker 1: the way here? Or are you happy to come here

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Speaker 1: and you actually meet people you actually want to see?

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Speaker 2: Well, I've actually been coming here since I ran Tech

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Speaker 2: Banking and Morgan Stanley back in the nineties and was

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Speaker 2: hunting for fees, and so I think it's sort of

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Speaker 2: become one stop shopping.

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Speaker 3: You make the trip and then.

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Speaker 2: You get to see people from Asia and Africa and

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Speaker 2: Middle East Europe.

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Speaker 3: So it's just that one stop shop.

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Speaker 1: Well, let's talk about your background now that you mentioned it.

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Speaker 1: Where did you grow up?

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Speaker 3: I grew up. I was born in Mainland, mostly grew

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Speaker 3: up in California, California.

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Speaker 1: Your father was a professor at Stanford or something like that.

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Speaker 3: My father actually was a Holocaust refugee.

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Speaker 2: So my father escaped from Vienna right after Krystal Knock

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Speaker 2: and made it to Palestine. He had no high school education,

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Speaker 2: He ended up in ruling in the British Army, fought

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Speaker 2: in the Bala Belloliman, and in the army.

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Speaker 3: Taught himself physics because he figured if he.

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Speaker 2: Survived, he needed something that somebody valued after the war

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Speaker 2: that actually that work, that plan worked. He ended up

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Speaker 2: getting to England, where I was born, and then eventually

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Speaker 2: got to the United States, who was sponsored by Senator Kennedy.

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Speaker 2: So he spent a tood career at Harvard and then

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Speaker 2: at Stanford. So I mostly grew up.

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Speaker 3: In California, California.

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Speaker 1: Okay, So you're in Stanford for a nice area, Silicon Valley.

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Speaker 1: Why would you want to go to a business school

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Speaker 1: at Wharton? Why did you go across the country to

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Speaker 1: go to business school? And why did you want to

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Speaker 1: go to business school to begin with? Why not be

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Speaker 1: a physicist like your father?

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Speaker 2: Well, I loved Wharton, so I'm not going to give

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Speaker 2: you that. You know, I thought I was going to

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Speaker 2: end up being First of all, I got married and

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Speaker 2: my husband was a lawyer on Wall Street, so I

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Speaker 2: was commuting. But I thought that I would go into investment.

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Speaker 2: But I thought I'd go into consulting. And then I

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Speaker 2: took this amazing mergers accounting class, kind of geeky, and

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Speaker 2: decided I was going to go in the mergers and acquisitions,

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Speaker 2: so ended up on East Coast, Okay.

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Speaker 1: So you ultimately became the CFO of Morgan Stanley Okay,

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Speaker 1: and many people thought you might go in the government someday,

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Speaker 1: and you actually could have been the CEO of Morgan Stanley.

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Speaker 1: Why would you leave the important world of finance for

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Speaker 1: something less significant like technology?

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Speaker 3: Why don't we going to do that?

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Speaker 2: You know, kind of right time, right place, Like when

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Speaker 2: I was the CFO of Morganton. I started in that

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Speaker 2: position January first, twenty ten, when James Gorbyn took over

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Speaker 2: as CEO, and I think he's an all star CEO,

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Speaker 2: absolutely amazing, great partner. And when we started it was

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Speaker 2: twenty ten, so after the financial crisis, but Morgan Stanley

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Speaker 2: was still very challenged. You know, Moody's was going to

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Speaker 2: downgrade the bank at one point. It was it was

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Speaker 2: kind of shaky, and I think that he and we togethered.

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Speaker 2: The team led this extraordinary kind of recovery and it

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Speaker 2: got to the point in twenty fifteen when I was

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Speaker 2: ready for the next chapter and I got this call,

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Speaker 2: so Google, it seemed okay, So.

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Speaker 1: All right, wade that move before we get to Google. Well,

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Speaker 1: you were at Morgan Stanley when the great meltdown, on

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Speaker 1: the Great financial Crisis of seven o eight occurred, and

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Speaker 1: it is said that, you know, people thought that Morgan

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Speaker 1: Stanley and Goldman Sachs and everybody else was going to go.

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Speaker 1: Wonder were you living through that and did you actually

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Speaker 1: think Morgan Stanley was going to make it at that time?

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Speaker 3: There were days I did not. It was bad.

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Speaker 2: So I was running financial institutions, banking at the time,

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Speaker 2: and probably the most meaningful part of my career was

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Speaker 2: when Hank Paulson called and said, I need advice.

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Speaker 3: I need some.

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Speaker 2: Bankers here, and so I went to and led a

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Speaker 2: team that worked on Fanny.

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Speaker 3: Freddy and then AIG. And those were very, very challenging.

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Speaker 2: Days and coming out of it at the you know,

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Speaker 2: we did Fanny Freddie and then we did AIG.

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Speaker 3: He put them into conservatorship.

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Speaker 2: And I had some more in Stanley John Mackwaco at

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Speaker 2: the time, and he said, okay.

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Speaker 3: You're in charge of liquidity. Figure out liquidity.

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Speaker 2: And of course days before what very much was running

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Speaker 2: out of liquidity there was no way to get liquidity.

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Speaker 2: In fact, one day we were trying to figure out

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Speaker 2: what to do and I thought the trading for I'm like,

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Speaker 2: can we maybe sell the chairs there were in Miller chairs?

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Speaker 2: I thought that might be a solution. That was supposed

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Speaker 2: to be funny, but it was actually really scary at

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Speaker 2: the time, and so no, it was hard. But we

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Speaker 2: did this whole series of different teams and it worked.

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Speaker 2: You know, MUFG came in, they were an incredible partner.

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Speaker 2: The government came in, we became a FED regulated bank.

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Speaker 2: But there were some very scary times and a lot

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Speaker 2: of important lessons.

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Speaker 1: One of the big challenges was that Mitsubishi agreed to

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Speaker 1: invest that I'd say twenty three dollars a share when

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Speaker 1: your stock was roughly at eight dollars a share. So

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Speaker 1: normally when somebody's stock is at eight, people don't usually

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Speaker 1: buy it at twenty three. So did you think them worked?

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Speaker 1: Mitsubishi was going to show up with that billion dollar

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Speaker 1: check at twenty three dollars a share.

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Speaker 2: We did, but there were times when it was questioned,

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Speaker 2: and there was one very fateful meeting John attended.

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Speaker 3: It's been written about and it was there.

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Speaker 2: Was a lot of back and forth between mug in Japanese,

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Speaker 2: and then there was one English word trust and at

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Speaker 2: that point he said, okay, this is going to work

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Speaker 2: and they were an incredible partner.

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Speaker 1: Okay, so he got that deal done. Then presumably some

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Speaker 1: headhunter called you up and said you should be the

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Speaker 1: CFO of Google and did you how did you tell

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Speaker 1: John Mack or James Gorman you were going to leave

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Speaker 1: to be the CFO of a tech company? Was that

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Speaker 1: easy to do?

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Speaker 3: So twenty fifteen, Morgan Stanley was a really good spot.

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Speaker 3: I happened to be with.

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Speaker 2: Bill Campbell, an icon and iconic leader in Silicon Valley.

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Speaker 2: He's been written about, It's the trillion dollar coach. He

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Speaker 2: coached Steve Jobs, Larry Sergei, Sundar Eric. So it's a

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Speaker 2: privilege to sit with him. And at the time I said,

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Speaker 2: you know, I'm ready for the next chapter, but the

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Speaker 2: one thing I'm not going to do is be CFO again.

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Speaker 2: We spent two hours in his living room and at

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Speaker 2: the end he said, okay, I heard you clearly not CFO.

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Speaker 2: And I said exactly, And he said, okay, So the

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Speaker 2: best I've got the best idea for you CFO of Google.

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Speaker 3: I immediately said, well, I thought that one.

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Speaker 1: That one is interesting, But did you tell them this

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Speaker 1: would mean you wouldn't be able to work with private

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Speaker 1: equity people as closely as.

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Speaker 2: You have been.

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Speaker 3: You know, somewhettimes, hardship in life is worthwhile.

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Speaker 1: Okay, so we're able to overcome that point.

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Speaker 3: I overcame that.

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Speaker 1: Okay. So what's it like moving from the East Coast,

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Speaker 1: where everything is finance and money, to the West Coast,

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Speaker 1: where everything is technology. Did you fit in right away?

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Speaker 1: And did you really know how to use all the

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Speaker 1: computer things that they give you to use?

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Speaker 3: So it was it was pretty fun.

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Speaker 2: There were plenty of times where I would sit around

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Speaker 2: in meetings and literally I would be googling terms, And

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Speaker 2: at one meeting, Larry Page actually caught me googling terms

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Speaker 2: and he kind of pointed that.

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Speaker 3: Out to other people in the room, which is a

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Speaker 3: little embarrassing.

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Speaker 2: But I figured there were some things that I could

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Speaker 2: do that they can do, and so it was a

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Speaker 2: learning curve. And my dad always he taught me at

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Speaker 2: a young age a.

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Speaker 3: Term that I've used constantly with my teams.

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Speaker 2: He said in his lab at Stanford, if a physicist

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Speaker 2: could not define a quark in under thirty seconds. They

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Speaker 2: didn't know what they were talking about, and so I

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Speaker 2: used the quark test all the time. If somebody's rambling

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Speaker 2: on and on and they can't get to the point,

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Speaker 2: they probably don't know what they're talking about.

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Speaker 3: They fail the Quark test. My finance team knows this

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Speaker 3: core test.

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Speaker 2: And at Google, I'm working with amazing computer scientists, so

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Speaker 2: they never fail the Park test. They can explain things

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Speaker 2: really clearly, which shoots up the learning curve.

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Speaker 3: But did you.

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Speaker 1: Understand what they were talking about from the beginning or

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Speaker 1: did you have a special tutor that's talking to technology

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Speaker 1: for I had actually run.

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Speaker 3: Tech banking into Google Publics.

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Speaker 1: I had a little sneak for you. So people who

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Speaker 1: use Google, I've always wondered this. Let's suppose I do

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Speaker 1: a Google search on something. Maybe I shouldn't be doing

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Speaker 1: a Google search on or something not that you ever do.

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Speaker 1: I wouldn't do that, but I just theoretically, can somebody

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Speaker 1: from Google, an officer like you look up what I've searched. No,

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Speaker 1: you cannot absolutely totally detected right and't protected even if

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Speaker 1: the government comes along.

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Speaker 2: We do not look at what you can go into

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Speaker 2: incognitimo that we do not look at what you search.

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Speaker 1: Okay. So the company for a long time was spelled

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Speaker 1: was called Google, and Google used to be spelled differently.

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Speaker 1: Why did they spell Google that way as opposed they

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Speaker 1: way it was originally spelled, which was E L Did

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Speaker 1: they not know that was spelled differently?

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Speaker 2: Well, there are a couple of stories around this, but

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Speaker 2: one of the stories that I think is true and

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Speaker 2: fun is that one of the early venture checks actually

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Speaker 2: wrote it that way. So they went with it.

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Speaker 1: Okay, So why did Google? Is that the brand name

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Speaker 1: that's working very well, companies making a lot of money

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Speaker 1: and so forth, But why did you need to go

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Speaker 1: to alphabet? And who came up with that name?

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Speaker 3: So Larry and.

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Speaker 2: Sergei had a vision about kind of the next iteration,

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Speaker 2: and there were a lot of different things that they

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Speaker 2: were investing in, the whole spirit of which is you

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Speaker 2: want to make sure you're investing for long term, investing

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Speaker 2: for the future. And in the earliest days, what they

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Speaker 2: did is they created.

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Speaker 3: Something called X.

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Speaker 2: It was the moonshot factory within Google Google X, and

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Speaker 2: it gave birth to things like Gmail and it was

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Speaker 2: really relevant for all of the type of innovation that

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Speaker 2: came out of Google, and by twenty fifteen their view was,

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Speaker 2: we want to be able to avoid distraction on Google.

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Speaker 2: Let Google do what it's going to do and create

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Speaker 2: another set of businesses that the founders could focus on

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Speaker 2: and really nurture growth outside of it. And so the

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Speaker 2: word is you would know better than anyone is alphabets and.

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Speaker 3: Say you put the two together. And that was the goal.

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Speaker 1: So it used to be when Google started, you had

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Speaker 1: what was called twenty percent time, right, so for twenty

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Speaker 1: percent of your time you could do whatever you wanted.

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Speaker 1: Theoretically it might be helpful in a company, but it

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Speaker 1: wasn't supposed to be necessarily. So do you still have

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Speaker 1: twenty percent time or they go away?

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Speaker 2: Well, And it was actually a little more structured than that.

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Speaker 2: The goal was if you had some great engineering idea

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Speaker 2: and you wanted to launch a new product, you could

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Speaker 2: do it in one of two ways.

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Speaker 3: You could leave or you could be.

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Speaker 2: Told, you know what, in twenty percent of your time,

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Speaker 2: why don't you go experiment with this and see if

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Speaker 2: you can grow it.

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Speaker 3: So a lot of the and having great.

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Speaker 2: Ideas constantly leaving the view as let's nurture the talent,

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Speaker 2: let's give people these growth opportunities.

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Speaker 3: Let's give it a go. And so that's what the

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Speaker 3: twenty percent time was.

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Speaker 1: Did any twenty percent time product ever get to the market.

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Speaker 2: Well, a Gmail is not an inconsequential billions of users.

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Speaker 2: Google Brain came out of that. It's our core part

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Speaker 2: of our AI business. And then we've continued to evolve it,

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Speaker 2: so it moved over to become x Weymo came out

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Speaker 2: of it. So there's quite quite a bit and quite

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Speaker 2: a bit of features and applications.

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Speaker 1: Thinking, waymo, are we going to have driver less cars

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Speaker 1: in our lifetime?

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Speaker 2: Well, I welcome everybody to come to San Francisco because

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Speaker 2: you can actually hail a Waimo in San Francisco, hop

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Speaker 2: in it and get where you want to go.

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Speaker 3: And it's pretty remarkable.

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Speaker 1: Have you done that? Absolutely brilliant safe.

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Speaker 2: It's so safe that the most fascinating part is within

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Speaker 2: about fifteen seconds people are bored because it's so safe there,

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Speaker 2: like they realize, you know, it's going to need a

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Speaker 2: helmet or in the nugget's safe if you need a

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Speaker 2: helmet with many drivers on the road, but you don't

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Speaker 2: need to know you don't need to. I see.

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Speaker 1: Okay, today you have a challenge that many people would

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Speaker 1: like to have but they don't have, which is, you've

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Speaker 1: got over one hundred billion dollars of cash, and so

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Speaker 1: are you going to invest that in private equity firms

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Speaker 1: or are you going to do new technology? What are

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Speaker 1: you going to do with one hundred billion dollars at

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Speaker 1: more than one hundred billion dollars of cash? And you know,

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Speaker 1: have you thought about that? You have people coming up

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Speaker 1: to you all the time with great ideas for that cash.

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Speaker 2: We do as you would imagine. So look, we're continuing

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Speaker 2: to invest in the business. There's a lot of extraordinary

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Speaker 2: upside in the business. And then we do make investments

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Speaker 2: and acquisitions, so do all of our peers. There's a

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Speaker 2: lot that's exciting going on in the world, and so

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Speaker 2: we're looking.

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Speaker 3: Across the board.

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Speaker 2: Starts within the business, then it goes to investments and acquisitions,

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Speaker 2: then obviously return to capital through a not in consequential

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Speaker 2: sharey purchase program.

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Speaker 1: So today, for people who are not experts on Google

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Speaker 1: and Google Search, Larry Page really developed the Page system

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Speaker 1: I guess it was called and it was unique. But

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Speaker 1: when he came to get the initial money in Silicon Valley,

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Speaker 1: people said, well, there's plenty of search engines out here,

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Speaker 1: were like twelve or thirteen search engine companies, and so

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Speaker 1: people didn't think it was anything so unique. What turned

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Speaker 1: out to be so unique about the page system that

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Speaker 1: it made Google such a powerful company.

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Speaker 2: I actually remember those days because I was one of

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Speaker 2: the people who said, why do we need It was

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Speaker 2: actually the eighth search engine?

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Speaker 3: Why do you need the eighth search engine?

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Speaker 2: And I was at Morgan Stanley at the time in

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Speaker 2: nineteen ninety eight running banking, and our research analyst, Mary Meeker,

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Speaker 2: an iconic analyst, pulled our team together and said, you

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Speaker 2: know what, let's do a test. Let's look at all

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Speaker 2: the search engines. Let's doe queries and see speed and

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Speaker 2: relevance of response. And I think she may have started

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Speaker 2: with that eight search engine question as well, but it

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Speaker 2: quickly rose to the top.

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Speaker 3: And that has been the ethos all along.

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Speaker 2: We still to this day have more than one hundred

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Speaker 2: product innovations every quarter. The whole idea is continue challenging

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Speaker 2: ourselves about how to make the product better, more relevant, faster,

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Speaker 2: and what's extraordinary. Sitting where we are today, is how

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Speaker 2: searches evolved. So back then it was ten blue links.

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Speaker 2: Wherever was old enough in this room to remember ten

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Speaker 2: blue links, That's what it was.

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Speaker 3: And then it went to image search, voice search, and

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Speaker 3: now multimobile search.

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Speaker 2: If I want your tie, I could take a picture

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Speaker 2: of your tie, and then I could just I can

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Speaker 2: lens it and I can find a.

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Speaker 3: Place to buy your tie.

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Speaker 2: So this whole evolution of search just keeps extending the

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Speaker 2: one way for search.

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Speaker 3: So it's very different obviously today than it was.

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Speaker 1: So it might be apocryphal. Maybe you could tell us

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Speaker 1: who may not have been there then. But in the

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Speaker 1: early days, when Google was getting its versus venture capital

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Speaker 1: money from the first venture capitalist, they said, you need

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Speaker 1: to have quote an adult, a CEO, somebody's been more experienced,

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Speaker 1: and Sergey and Larry weren't maybe thrilled with doing that.

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Speaker 1: But it is said that they waited a while and

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Speaker 1: they eventually did get a CEO. But until they got one,

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Speaker 1: the venture capitalists were thinking about taking the money back.

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Speaker 1: You ever heard of this story.

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Speaker 3: I have not heard they were going to take it back.

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Speaker 2: I've heard there were a certain aqua position ideas that,

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Speaker 2: thank goodness, never happened, but it was great when Eric

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Speaker 2: came in and really worked with the founders in a

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Speaker 2: really close way.

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Speaker 1: But today, how many employees does Alphabet have down.

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Speaker 3: One hundred and eighty thousand?

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Speaker 1: And are they all in Silicon Valley or where?

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Speaker 3: Oh, we have them right up from Donos here in Zurich.

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Speaker 3: We have them all over the globe.

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Speaker 2: In fact, we're growing faster outside of Silicon Valley than

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Speaker 2: in Silicon Valley.

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Speaker 1: And of the one hundred and eighty thousand, can you say,

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Speaker 1: or do you break it out publicly how many of

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Speaker 1: them are related to search?

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Speaker 3: We don't break that up publicly.

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Speaker 1: We'll just tell us.

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Speaker 3: We have an incredibly talented group of.

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Speaker 1: People were focused on search, and you have you're still

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Speaker 1: hiring people.

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Speaker 2: We are very as we've talked about quite a bit,

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Speaker 2: we've been very focused on what we call durably re

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Speaker 2: engineering the cost base, slowing the pace of headcount growth,

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Speaker 2: really trying to optimize within our various areas.

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Speaker 3: So it's a more measure.

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Speaker 1: Now let's talk about art of intelligence. Artificial intelligence has

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Speaker 1: gotten a lot of publicity in the last year or so,

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Speaker 1: and open ai has got an enormous amount of it,

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Speaker 1: and they have an affiliation with another technology company. I

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Speaker 1: can't remember the name of it.

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Speaker 3: I've heard that another one.

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Speaker 1: But do you have your own kind of open AI

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Speaker 1: company or do you do it all internally? And what

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Speaker 1: do you do to compete with open ai and this

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Speaker 1: other technology company.

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Speaker 2: So we've had we've been infusing product at Google with

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Speaker 2: AI for more than a decade. In fact, billions of

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Speaker 2: people today are benefiting from AI across our products. It's

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Speaker 2: benefiting what you see in search, in maps, and commerce

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Speaker 2: and YouTube. You know, I just mentioned multimodal search, the

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Speaker 2: ability to search with your camera when you search for

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Speaker 2: your kids and photos, that's AI. So AI has continued

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Speaker 2: to be a way to enhance what the product experience is.

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Speaker 2: And we've done that historically through two groups within one

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Speaker 2: Google Brain I already mentioned, and the other is Deeplined,

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Speaker 2: an extraordinary acquisition back many years ago, led by an

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Speaker 2: extraordinary entrepreneur Demesistatist. And we've put the two together last year,

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Speaker 2: which has been really exciting, and so we are building

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Speaker 2: on that foundation that has been an experience for the

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Speaker 2: last decade.

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Speaker 1: Okay, so what's the excitement of working in technology in

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Speaker 1: Silicon Valley? Is it even more exciting than working in

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Speaker 1: finance or not quite as exciting?

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Speaker 3: But okay, it's hard to believe it's more exciting.

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Speaker 2: Ed I'm really living in the most extraordinary time with AI.

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Speaker 3: Bilgas just said that. I completely agree.

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Speaker 2: Engineers who've been at Google since inception are saying that

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Speaker 2: this is the most exciting time in computer science in

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Speaker 2: our lifetime, which always strikes me as profound because Google's

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Speaker 2: done okay, And what's extraordinary about it really goes to

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Speaker 2: building on this decade of innovative work in AI, and

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Speaker 2: so where are we now at What we're doing is

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Speaker 2: we're addressing some of the most profound social challenges with

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Speaker 2: AI and rays they're transformative. So giving you an excamo examples,

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Speaker 2: I think that one of the extraordinary places for all

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Speaker 2: of us, and we've heard a lot about it here

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Speaker 2: over lunch, is healthcare. And part of the reason is

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Speaker 2: it's the ability with AI to aggregate so much data

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Speaker 2: that you can actually have a level of diagnosis that

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Speaker 2: is better than what specialists can do.

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Speaker 3: So one example breast cancer.

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Speaker 2: Back in twenty fifteen, Google had a breakthrough in detection

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Speaker 2: early detection of metastatic breast cancer. One seven women will

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Speaker 2: be diagnosed with breast cancer. I was one of those.

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Speaker 2: I've had breast cancer twice, so when I heard about this,

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Speaker 2: I did the only rational thing. I called my oncologist

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Speaker 2: at Memorial Song Kettering and I said, is this really

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Speaker 2: as important as I hope? And he said unequivocally, because

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Speaker 2: only with AI can we democratize healthcare. It's the only

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Speaker 2: way that oncologists everywhere, radiologists everywhere, all of the medical

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Speaker 2: profession has the ability to leverage the insight that AI

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Speaker 2: will give you through scans reviewing a million scans.

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Speaker 3: We're doing the same in other forms of cancer. We're

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Speaker 3: doing it with something.

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Speaker 2: Called diabetic retinopathy blindness cause through diabetes, which can be

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Speaker 2: prevented if diagnosed early enough. And so I think that

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Speaker 2: when you look at the impact Devita, this is what

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Speaker 2: motivates our engineers. We're singing healthcare, We're singing in education.

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Speaker 2: We're seeing it with food scarcity. You can improve crop

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Speaker 2: yields by looking at pest issues in farming. We're looking

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Speaker 2: at so many different ways that AI can make a

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Speaker 2: difference on the most profound issues. One last one, because

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Speaker 2: you asked to my excited about it, Yes, it's better

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Speaker 2: than even finance climate change. You know sls, crisis alerts extraordinary.

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Speaker 2: We've seen the impact of buyers and flooding. Two earn

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Speaker 2: fifty million people a year affected by flooding.

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Speaker 3: But with AI, we.

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Speaker 2: Can predict and r with seven days notice where the

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Speaker 2: waterflows will be to get people out of harm's way.

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Speaker 3: So this is not science fiction. This is here today now.

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Speaker 1: On climate change. To be realistic about it. These are

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Speaker 1: things that you think that AI can really make us

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Speaker 1: make more readily, make us able to solve climate changes.

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Speaker 1: At your point, you think we can.

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Speaker 3: Well, there's both adaptation and mitigation.

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Speaker 2: So around climate change we have a whole other set

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Speaker 2: of efforts going on.

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Speaker 3: So, for example, one of.

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Speaker 2: The major sources of emissions is what you see right

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Speaker 2: out the window here, start stop from cars. We have

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Speaker 2: something called Project green Light which streamlines that so you

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Speaker 2: don't have the start stops. We have something else that

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Speaker 2: looks at planes, major source of carbon footprint out of contrails,

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Speaker 2: what many of us think are the beautiful white plumes

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Speaker 2: off the back. You can adjust flight patterns and reduce

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Speaker 2: carbon foot So the short answer is yes, and it's

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Speaker 2: happening today.

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Speaker 3: It's not a hope for science fiction.

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Speaker 1: You've been public about your breast cancer. You've talked about it,

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Speaker 1: written about it, and so forth. Why did you go

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Speaker 1: public about it? Many women say they don't want it

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Speaker 1: to be known that they might have breast cancer. Maybe

445
00:20:15,280 --> 00:20:17,320
Speaker 1: that's right or wrong. But why were you so willing

446
00:20:17,359 --> 00:20:19,000
Speaker 1: to be public about it?

447
00:20:19,000 --> 00:20:20,280
Speaker 3: It is a really personal thing.

448
00:20:20,320 --> 00:20:22,199
Speaker 2: And when I was first diagnosed, I didn't want to

449
00:20:22,200 --> 00:20:24,359
Speaker 2: talk about it. I was at a bank on a

450
00:20:24,359 --> 00:20:27,240
Speaker 2: few women, you know, I was bald, and.

451
00:20:28,000 --> 00:20:30,119
Speaker 3: Like, it's not what you want to talk about. I

452
00:20:30,119 --> 00:20:31,000
Speaker 3: got to the point.

453
00:20:30,760 --> 00:20:33,080
Speaker 2: Where I realized, in this day and age, if you

454
00:20:33,119 --> 00:20:37,000
Speaker 2: get the right care, actually these diseases are manageable and

455
00:20:37,040 --> 00:20:38,639
Speaker 2: the scariest part is not knowing.

456
00:20:39,280 --> 00:20:43,320
Speaker 3: And so to me it was important to actually.

457
00:20:43,640 --> 00:20:46,520
Speaker 2: Make it clear this is manageable, you can get through it,

458
00:20:46,680 --> 00:20:48,800
Speaker 2: and to actually be a resource for people.

459
00:20:49,160 --> 00:20:52,359
Speaker 1: So for many women, you're a role model. You have

460
00:20:52,480 --> 00:20:55,600
Speaker 1: a successful career in finance and technology. You were on

461
00:20:55,680 --> 00:20:57,119
Speaker 1: your first husband.

462
00:20:57,440 --> 00:21:00,720
Speaker 3: Right, yeah, yeah, hang on hanging on right.

463
00:21:01,040 --> 00:21:04,560
Speaker 1: So, and you have three kids, and so you've done

464
00:21:04,560 --> 00:21:06,879
Speaker 1: it all, You've had it all. You you know, have

465
00:21:06,960 --> 00:21:10,399
Speaker 1: a successful career of successful marriage, three healthy, happy kids,

466
00:21:11,640 --> 00:21:13,879
Speaker 1: Can you tell us something that doesn't make us feel

467
00:21:14,000 --> 00:21:16,919
Speaker 1: jealous about you because you're I mean you're you know

468
00:21:17,320 --> 00:21:19,520
Speaker 1: everybody can't be as good as you. So make us

469
00:21:19,520 --> 00:21:22,159
Speaker 1: feel that everything isn't perfect for you, leaving aside the

470
00:21:22,160 --> 00:21:25,040
Speaker 1: breast cancer, so that everybody else doesn't feel like they're

471
00:21:25,080 --> 00:21:26,879
Speaker 1: not going to be able to live up to your standards.

472
00:21:27,800 --> 00:21:32,720
Speaker 2: Oh Man, Olier, Indians like I think that one of

473
00:21:32,760 --> 00:21:37,280
Speaker 2: the most important lessons I learned early in my career.

474
00:21:37,480 --> 00:21:40,440
Speaker 3: You know, as a woman in banking, there weren't many

475
00:21:40,480 --> 00:21:43,400
Speaker 3: of us. It wasn't the easiest environment.

476
00:21:44,119 --> 00:21:49,520
Speaker 2: There were a lot of men I've now gently decided

477
00:21:49,600 --> 00:21:54,080
Speaker 2: to call blockheads, but you know they were worse than blockheads.

478
00:21:54,080 --> 00:21:58,000
Speaker 3: And they made it difficult, and you learned to be resilient.

479
00:21:58,520 --> 00:22:00,960
Speaker 2: One thing is I was going to outline ask them

480
00:22:01,320 --> 00:22:03,439
Speaker 2: and that would be the joy that came from it.

481
00:22:03,800 --> 00:22:05,280
Speaker 3: Unfortunately, there are obviously a lot of.

482
00:22:05,280 --> 00:22:08,840
Speaker 2: Extraordinary men at Morgan Stanley and I want to have

483
00:22:08,880 --> 00:22:10,760
Speaker 2: senior women in the day, and there are more now.

484
00:22:11,240 --> 00:22:14,440
Speaker 3: And so I learned to chart my career. I went

485
00:22:14,480 --> 00:22:16,240
Speaker 3: to people who would take a risk on me, and

486
00:22:16,280 --> 00:22:19,000
Speaker 3: I said, what's my highest and best use? And they opened.

487
00:22:18,600 --> 00:22:22,160
Speaker 2: Doors that I didn't know existed. And to me that's

488
00:22:22,200 --> 00:22:25,679
Speaker 2: the most important is those hard days, bad lessons. I

489
00:22:25,760 --> 00:22:27,760
Speaker 2: just chalk them up to being lessons, so I don't

490
00:22:27,800 --> 00:22:29,480
Speaker 2: actually record them.

491
00:22:29,520 --> 00:22:31,639
Speaker 1: So for a young woman that's watching this or a

492
00:22:31,680 --> 00:22:34,720
Speaker 1: young man. And what are the recommendation you have to

493
00:22:34,720 --> 00:22:37,600
Speaker 1: get ahead in the finance world, technology world? Is it

494
00:22:37,600 --> 00:22:40,040
Speaker 1: be smarter than other people, be nicer than other people,

495
00:22:40,240 --> 00:22:44,639
Speaker 1: be harder working. What is it that takes to be successful.

496
00:22:45,080 --> 00:22:47,960
Speaker 2: Well, there's no substitute for hard work, because the hard

497
00:22:48,000 --> 00:22:50,680
Speaker 2: work actually gets you swared up the learning curve faster.

498
00:22:50,880 --> 00:22:52,960
Speaker 3: So certainly that's one of them.

499
00:22:53,040 --> 00:22:55,720
Speaker 2: I think the other I've already said, chart your career,

500
00:22:56,040 --> 00:22:58,000
Speaker 2: work for somebody who's going to take a risk on

501
00:22:58,040 --> 00:22:59,800
Speaker 2: you and give you runway.

502
00:23:00,000 --> 00:23:01,960
Speaker 3: Importantly, we need to do that for someone.

503
00:23:02,080 --> 00:23:03,640
Speaker 2: So at one point, when I was asked to run

504
00:23:03,680 --> 00:23:07,680
Speaker 2: technology equity capital markets on the equity trading floor, a

505
00:23:07,800 --> 00:23:10,960
Speaker 2: senior partner called me into his office and he said,

506
00:23:10,960 --> 00:23:12,800
Speaker 2: I will be your seat, I will be your air cover.

507
00:23:13,320 --> 00:23:14,960
Speaker 2: All the guys said, we're going to say use these

508
00:23:14,960 --> 00:23:17,159
Speaker 2: military terms. There a lot of military guys, but it

509
00:23:17,200 --> 00:23:19,240
Speaker 2: was a good one. I will be your air cover.

510
00:23:19,640 --> 00:23:21,600
Speaker 2: I think you will sort, but if you stumble, I'm

511
00:23:21,640 --> 00:23:24,600
Speaker 2: here to be your air cover. I think everyone needs

512
00:23:24,640 --> 00:23:26,280
Speaker 2: air cover, and I think we all.

513
00:23:26,119 --> 00:23:29,520
Speaker 3: Need to be air cover. And the other is keep

514
00:23:29,600 --> 00:23:30,760
Speaker 3: learning and keep growing.

515
00:23:30,800 --> 00:23:33,320
Speaker 2: And when you're plateauing, my line was what's my highest

516
00:23:33,320 --> 00:23:38,440
Speaker 2: and best use and don't do it on a specific timeline.

517
00:23:37,640 --> 00:23:39,159
Speaker 3: But keep evolving.

518
00:23:39,320 --> 00:23:40,679
Speaker 2: And if you go to the right people, they'll keep

519
00:23:40,720 --> 00:23:43,119
Speaker 2: opening doors and take those doors. And then finally use

520
00:23:43,119 --> 00:23:43,639
Speaker 2: your voice.

521
00:23:43,840 --> 00:23:46,720
Speaker 1: So what do you do when you're not working on technology,

522
00:23:47,560 --> 00:23:50,919
Speaker 1: being a wife, being a mother, you have you're a

523
00:23:50,960 --> 00:23:53,240
Speaker 1: tennis player or a golfer, what do you do for

524
00:23:53,359 --> 00:23:55,840
Speaker 1: relaxation because you have time for relaxation.

525
00:23:56,760 --> 00:23:58,399
Speaker 2: Well, I kind of e merge them because I know

526
00:23:58,520 --> 00:24:00,920
Speaker 2: there's nothing more joyful to me than going on hikes

527
00:24:00,960 --> 00:24:02,959
Speaker 2: with my kids or bike rides with my kids.

528
00:24:04,359 --> 00:24:07,679
Speaker 3: And so it's you know, it's a lot of that, okay.

529
00:24:07,920 --> 00:24:10,359
Speaker 1: And so is there anything that you are Your parents

530
00:24:10,400 --> 00:24:13,399
Speaker 1: alive now they are not, And did they live to

531
00:24:13,400 --> 00:24:16,160
Speaker 1: see your success before they passed away?

532
00:24:16,800 --> 00:24:17,240
Speaker 3: They did.

533
00:24:17,560 --> 00:24:19,640
Speaker 2: My mom, actually, when I was a young kid, said

534
00:24:19,960 --> 00:24:22,520
Speaker 2: she was a psychologist and she said, what's really important

535
00:24:22,520 --> 00:24:25,760
Speaker 2: for women is have your own identity. And a career

536
00:24:25,800 --> 00:24:27,399
Speaker 2: outside of the home. She told me that when I

537
00:24:27,400 --> 00:24:29,800
Speaker 2: was eight, my little sister was six. For some reason,

538
00:24:29,840 --> 00:24:30,680
Speaker 2: she thought that's.

539
00:24:30,520 --> 00:24:33,200
Speaker 3: The time you need to send that message. So I'm

540
00:24:33,240 --> 00:24:34,800
Speaker 3: grateful to her for that message.

541
00:24:34,920 --> 00:24:38,399
Speaker 1: Okay, and your father, did he ever say this is

542
00:24:38,400 --> 00:24:40,040
Speaker 1: better than being a physicist? What you're doing?

543
00:24:40,840 --> 00:24:42,840
Speaker 3: My dad was pretty remarkable. You know.

544
00:24:43,000 --> 00:24:46,840
Speaker 2: The taling of that story about his journey from no

545
00:24:46,920 --> 00:24:49,239
Speaker 2: high school education to a PhD in a career at

546
00:24:49,280 --> 00:24:53,000
Speaker 2: Stanford is you said education is your passport for freedom.

547
00:24:53,480 --> 00:24:56,880
Speaker 2: And so the only point he impressed on us over

548
00:24:56,960 --> 00:25:02,160
Speaker 2: and over was really focused on education, keep opening.

549
00:25:01,920 --> 00:25:03,720
Speaker 3: Doors and take risks.

550
00:25:03,800 --> 00:25:05,560
Speaker 2: If he didn't take the risk he took to get

551
00:25:05,640 --> 00:25:09,160
Speaker 2: himself out of Austria to teach himself physics, he would

552
00:25:09,240 --> 00:25:09,600
Speaker 2: have made it.

553
00:25:09,640 --> 00:25:12,280
Speaker 3: And he was so grateful to get to the United States.

554
00:25:12,359 --> 00:25:14,600
Speaker 2: So if there was anything else, it was that the

555
00:25:14,640 --> 00:25:16,760
Speaker 2: life that he never expected he would have, and then

556
00:25:16,800 --> 00:25:17,479
Speaker 2: to have a family,