1 00:00:03,520 --> 00:00:05,720 Speaker 1: In recent years, one of the most powerful people in 2 00:00:05,760 --> 00:00:09,040 Speaker 1: the financial and technology worlds has been Ruth Parratt. She 3 00:00:09,160 --> 00:00:12,080 Speaker 1: served as chief financial officer for Morgan Stanley and then 4 00:00:12,119 --> 00:00:15,360 Speaker 1: the chief financial officer for Google and Alphabet. She now 5 00:00:15,440 --> 00:00:19,119 Speaker 1: serves as president and Chief Investment Officer for Alphabet. I 6 00:00:19,160 --> 00:00:21,760 Speaker 1: sat down with her recently in Davos to talk about 7 00:00:21,760 --> 00:00:23,880 Speaker 1: what she's going to do in her new position and 8 00:00:23,920 --> 00:00:26,000 Speaker 1: how she's going to invest more than one hundred billion 9 00:00:26,040 --> 00:00:33,040 Speaker 1: dollars that Alphabet now has. So we're very pleased to 10 00:00:33,080 --> 00:00:36,400 Speaker 1: have Ruth Parratt here. Ruth, as you may know, has 11 00:00:36,440 --> 00:00:40,000 Speaker 1: recently been promoted. She for almost the last decade has 12 00:00:40,040 --> 00:00:44,120 Speaker 1: been the CFO of Google and Alphabet, and now she 13 00:00:44,159 --> 00:00:47,040 Speaker 1: still has that title, but she's now also the president 14 00:00:47,040 --> 00:00:49,600 Speaker 1: and chief Investment officer for Alphabet. 15 00:00:49,680 --> 00:00:50,160 Speaker 2: Is that right? 16 00:00:50,280 --> 00:00:51,640 Speaker 3: I am, And it's great to be here with you. 17 00:00:51,840 --> 00:00:55,680 Speaker 1: So you have three jobs, CFO, President, you get three 18 00:00:55,720 --> 00:00:56,440 Speaker 1: salaries for that. 19 00:00:57,840 --> 00:01:01,720 Speaker 4: I think I'm doing okay, okay, So. 20 00:01:03,080 --> 00:01:05,600 Speaker 1: Everybody wants to talk to you here because you've got 21 00:01:05,600 --> 00:01:07,119 Speaker 1: a lot of money. You've got over one hundred million 22 00:01:07,120 --> 00:01:09,760 Speaker 1: dollars of cash to invest, so people want to see you. 23 00:01:10,840 --> 00:01:12,840 Speaker 1: Why do you come to Davos because people are just 24 00:01:12,880 --> 00:01:15,280 Speaker 1: going to be bombarding you give me money for this 25 00:01:15,440 --> 00:01:17,639 Speaker 1: or that. Is it really worth the effort to slept 26 00:01:17,680 --> 00:01:19,440 Speaker 1: all the way here or are you happy to come 27 00:01:19,440 --> 00:01:22,240 Speaker 1: here and you actually meet people you actually want to see? 28 00:01:22,440 --> 00:01:24,760 Speaker 4: Well, I've actually been coming here since I ran tech 29 00:01:24,800 --> 00:01:27,880 Speaker 4: banking at Morgan Stanley back in the nineties and was 30 00:01:27,959 --> 00:01:30,000 Speaker 4: hunting for fees, and so I think it's sort. 31 00:01:29,800 --> 00:01:32,759 Speaker 3: Of become one stop shopping. You make the trip and. 32 00:01:32,680 --> 00:01:35,200 Speaker 4: Then you get to see people from Asia and Africa, 33 00:01:35,360 --> 00:01:38,600 Speaker 4: Middle East, Europe, so it's just that one stop shop. 34 00:01:38,880 --> 00:01:41,400 Speaker 1: Well, let's talk about your background now that you mentioned it. 35 00:01:41,840 --> 00:01:42,800 Speaker 1: Where did you grow up? 36 00:01:44,160 --> 00:01:46,600 Speaker 3: I grew up. I was born in England, mostly grew. 37 00:01:46,520 --> 00:01:48,880 Speaker 1: Up in California, California. Your father was a professor at 38 00:01:48,880 --> 00:01:50,200 Speaker 1: Stanford or something like that. 39 00:01:50,280 --> 00:01:52,560 Speaker 3: My father actually was a Holocaust refugee. 40 00:01:52,680 --> 00:01:56,800 Speaker 4: So my father escaped from Vienna right after Krystal Knock 41 00:01:57,280 --> 00:02:00,840 Speaker 4: and made it to Palestine high school education. 42 00:02:00,880 --> 00:02:01,840 Speaker 3: He ended up in enrolling in the. 43 00:02:01,840 --> 00:02:05,520 Speaker 4: British Army, fought in the Balla Bella Laman and in 44 00:02:05,560 --> 00:02:08,720 Speaker 4: the army taught himself physics because he figured if he 45 00:02:08,919 --> 00:02:13,480 Speaker 4: survived he needed something that somebody valued after the war 46 00:02:13,840 --> 00:02:16,440 Speaker 4: that actually that work, that plan worked. He ended up 47 00:02:16,480 --> 00:02:19,480 Speaker 4: getting to England, where I was born, and then eventually 48 00:02:19,639 --> 00:02:22,240 Speaker 4: got to the United States, who was sponsored by Senator Kennedy. 49 00:02:22,280 --> 00:02:24,240 Speaker 4: So he spent his whole career at Harvard and then 50 00:02:24,280 --> 00:02:25,600 Speaker 4: at Stamford. So I mostly grew up in. 51 00:02:25,600 --> 00:02:29,400 Speaker 1: California, California, Okay, So you're in Stanford for a nice area, 52 00:02:29,480 --> 00:02:32,400 Speaker 1: Silicon Valley. Why would you want to go to a 53 00:02:32,520 --> 00:02:34,920 Speaker 1: business school at Wharton? Why did you go across the 54 00:02:34,960 --> 00:02:36,920 Speaker 1: country to go to business school? And why did you 55 00:02:36,960 --> 00:02:38,560 Speaker 1: want to go to business school to begin with? Why 56 00:02:38,560 --> 00:02:39,919 Speaker 1: not be a physicist like your father? 57 00:02:40,240 --> 00:02:40,480 Speaker 3: Well? 58 00:02:40,560 --> 00:02:43,200 Speaker 4: I loved Wharton, so I'm not going to give you that. 59 00:02:44,600 --> 00:02:46,280 Speaker 4: You know, I thought I was going to end up 60 00:02:46,320 --> 00:02:48,560 Speaker 4: being First of all, I I got married. My husband 61 00:02:48,639 --> 00:02:50,440 Speaker 4: was a lawyer on Wall Street, so I was commuting. 62 00:02:51,000 --> 00:02:53,400 Speaker 4: But I thought that I would go into investment. I 63 00:02:53,400 --> 00:02:55,280 Speaker 4: thought I'd go into consulting, and then I took this 64 00:02:55,320 --> 00:03:00,720 Speaker 4: amazing merger's accounting class, kind of geeky, and decided I 65 00:03:00,760 --> 00:03:02,239 Speaker 4: was going to go into mergers and acquisitions. 66 00:03:02,240 --> 00:03:03,440 Speaker 3: So ended up on the East Coast. 67 00:03:03,600 --> 00:03:03,880 Speaker 2: Okay. 68 00:03:03,960 --> 00:03:06,919 Speaker 1: So she ultimately became the CFO of Morgan Stanley. Okay, 69 00:03:07,200 --> 00:03:09,840 Speaker 1: and many people thought you might go in the government someday, 70 00:03:09,840 --> 00:03:12,120 Speaker 1: and you actually could have been the CEO of Morgan Stanley. 71 00:03:12,160 --> 00:03:14,880 Speaker 1: Why would you leave the important world of finance for 72 00:03:15,000 --> 00:03:16,800 Speaker 1: something less significant like technology? 73 00:03:16,800 --> 00:03:18,200 Speaker 2: Why would you do that? 74 00:03:20,520 --> 00:03:22,760 Speaker 4: You know, kind of right time, right place, Like when 75 00:03:22,800 --> 00:03:25,240 Speaker 4: I was the CFO of Morgan Stanley. I started in 76 00:03:25,280 --> 00:03:28,000 Speaker 4: that position January first, twenty ten, when James Gorman took 77 00:03:28,000 --> 00:03:31,360 Speaker 4: over as CEO, and I think he's an all star CEO, 78 00:03:31,480 --> 00:03:35,760 Speaker 4: absolutely amazing, great partner. And when we started, it was 79 00:03:36,240 --> 00:03:38,880 Speaker 4: twenty ten, so after the financial crisis, but Morgan Stanley 80 00:03:38,960 --> 00:03:41,600 Speaker 4: was still very challenged. You know, Moody's was going to 81 00:03:41,720 --> 00:03:44,840 Speaker 4: downgrade the bank at one point. It was it was 82 00:03:44,920 --> 00:03:45,600 Speaker 4: kind of shaky. 83 00:03:45,720 --> 00:03:47,480 Speaker 3: And I think that he and. 84 00:03:47,640 --> 00:03:51,440 Speaker 4: We, together the team, led this extraordinary kind of recovery 85 00:03:51,520 --> 00:03:53,160 Speaker 4: and it got to the point in twenty fifteen where 86 00:03:53,160 --> 00:03:54,360 Speaker 4: I was ready for the next chapter, and then I 87 00:03:54,360 --> 00:03:55,280 Speaker 4: got this call. 88 00:03:55,560 --> 00:03:59,160 Speaker 3: Right of Google. It seemed okay, so all right, wade that. 89 00:03:59,120 --> 00:04:01,240 Speaker 1: Move before we get the good Well, you were at 90 00:04:01,280 --> 00:04:04,240 Speaker 1: Morgan's Stanley when the great meltdown, the Great Financial Crisis 91 00:04:04,240 --> 00:04:06,840 Speaker 1: of seven o eight occurred, and it is said that 92 00:04:07,680 --> 00:04:10,200 Speaker 1: people thought that Morgan Stanley and Goldman Sachs and everybody 93 00:04:10,200 --> 00:04:12,640 Speaker 1: else was going to go under. Were you living through 94 00:04:12,680 --> 00:04:14,560 Speaker 1: that and did you actually think Morgan Stanley was going 95 00:04:14,600 --> 00:04:15,680 Speaker 1: to make it at that time? 96 00:04:16,320 --> 00:04:19,200 Speaker 3: There were days I did not. It was bad. 97 00:04:20,120 --> 00:04:22,560 Speaker 4: So I was running financial institutions banking at the time, 98 00:04:22,600 --> 00:04:24,680 Speaker 4: and probably the most meaningful part of my career was 99 00:04:24,720 --> 00:04:27,880 Speaker 4: when Hank Paulson called and said, I need advice. I 100 00:04:27,920 --> 00:04:31,560 Speaker 4: need some bankers here, and so I went and led 101 00:04:31,600 --> 00:04:34,919 Speaker 4: a team that worked on Fanny Freddy and then AIG 102 00:04:35,120 --> 00:04:38,680 Speaker 4: and those were very, very challenging days. 103 00:04:39,160 --> 00:04:42,560 Speaker 3: And coming out of it at the we. 104 00:04:42,480 --> 00:04:45,280 Speaker 4: Did Fanny Freddy and then we did AIG, put them 105 00:04:45,279 --> 00:04:48,599 Speaker 4: into conservatorship, and I had some Morgan Stanley. John mackwa 106 00:04:48,680 --> 00:04:51,279 Speaker 4: CEO at the time, and he said, okay, you're in 107 00:04:51,360 --> 00:04:55,640 Speaker 4: charge of liquidity, figure out liquidity. And of course days 108 00:04:55,640 --> 00:04:58,560 Speaker 4: before what very much was running out of liquidity, there 109 00:04:58,600 --> 00:05:00,840 Speaker 4: was no way to get liquidity. In fact, one day 110 00:05:00,960 --> 00:05:02,840 Speaker 4: we were trying to figure out what to do when 111 00:05:02,839 --> 00:05:04,240 Speaker 4: I was on the trading floor and I'm like, can 112 00:05:04,279 --> 00:05:05,880 Speaker 4: we maybe sell the chairs? 113 00:05:05,880 --> 00:05:07,080 Speaker 3: There were Herman Miller chairs. 114 00:05:07,120 --> 00:05:09,360 Speaker 4: I thought that might be a solution that was supposed 115 00:05:09,360 --> 00:05:11,160 Speaker 4: to be funny, but it was actually. 116 00:05:10,800 --> 00:05:14,400 Speaker 3: Really scary at the time, and so no, it was hard. 117 00:05:14,600 --> 00:05:17,800 Speaker 4: But we did this whole series of different teams and 118 00:05:18,560 --> 00:05:20,760 Speaker 4: it worked. You know, MUFG came in, they were an 119 00:05:20,800 --> 00:05:23,719 Speaker 4: incredible partner. The government came in, we became a Fed 120 00:05:23,800 --> 00:05:26,680 Speaker 4: regulated bank. But there were some very scary times and 121 00:05:26,680 --> 00:05:27,760 Speaker 4: a lot of important lessons. 122 00:05:27,839 --> 00:05:29,479 Speaker 2: Okay, so you got that deal done. 123 00:05:29,680 --> 00:05:32,960 Speaker 1: Then presumably some headhunter called you up and said you 124 00:05:33,040 --> 00:05:36,760 Speaker 1: should be the CFO of Google And did you how 125 00:05:36,760 --> 00:05:39,000 Speaker 1: did you tell John Mack or James Gorman you were 126 00:05:39,000 --> 00:05:41,400 Speaker 1: going to leave to be the CFO of a tech company? 127 00:05:41,600 --> 00:05:42,320 Speaker 2: Was that easy to do? 128 00:05:43,560 --> 00:05:47,440 Speaker 4: So twenty fifteen, Morgan Stanley was in a really good spot. 129 00:05:47,720 --> 00:05:50,440 Speaker 4: I happened to be with Bill Campbell, an and iconic 130 00:05:50,520 --> 00:05:53,120 Speaker 4: leader in Silicon Valley. He's been written about as the 131 00:05:53,120 --> 00:05:58,440 Speaker 4: trillion dollar coach. He coached Steve Jobs, Larry Sergei, Sundar Eric. 132 00:05:58,520 --> 00:06:00,520 Speaker 3: So it's a privileged with them. 133 00:06:01,080 --> 00:06:02,839 Speaker 4: And at the time I said, you know, I'm ready 134 00:06:02,880 --> 00:06:04,320 Speaker 4: for the next chapter, but the one thing I'm not 135 00:06:04,320 --> 00:06:06,599 Speaker 4: going to do is be CFO again. We spent two 136 00:06:06,720 --> 00:06:10,159 Speaker 4: hours in his living room and at the end, he said, okay, 137 00:06:10,279 --> 00:06:13,320 Speaker 4: I heard you clearly not CFO, And I said exactly, 138 00:06:13,760 --> 00:06:14,680 Speaker 4: and he said, okay. 139 00:06:14,520 --> 00:06:16,960 Speaker 3: So the best I've got the best idea for CFO of. 140 00:06:16,920 --> 00:06:21,120 Speaker 4: Google, And of course I immediately said, well, I hadn't 141 00:06:21,120 --> 00:06:21,720 Speaker 4: thought of that one. 142 00:06:21,760 --> 00:06:22,880 Speaker 3: That one is interesting. 143 00:06:24,040 --> 00:06:25,640 Speaker 1: But did you tell him this would mean you wouldn't 144 00:06:25,640 --> 00:06:27,880 Speaker 1: be able to work with private equity people as closely 145 00:06:27,920 --> 00:06:28,440 Speaker 1: as you had been. 146 00:06:28,839 --> 00:06:31,520 Speaker 3: You know, somewhat. Times hardship in life is worthwhile. 147 00:06:31,760 --> 00:06:34,320 Speaker 1: So what's it like moving from the East Coast, where 148 00:06:34,320 --> 00:06:37,160 Speaker 1: everything is finance and money, to the West Coast, where 149 00:06:37,160 --> 00:06:38,120 Speaker 1: everything is technology. 150 00:06:38,120 --> 00:06:39,200 Speaker 2: Did you fit in right away? 151 00:06:39,400 --> 00:06:41,040 Speaker 1: And did you really know how to use all the 152 00:06:41,080 --> 00:06:43,240 Speaker 1: computer things that they give you to use? 153 00:06:45,360 --> 00:06:49,120 Speaker 3: So it was it was It was pretty fun. 154 00:06:49,480 --> 00:06:51,400 Speaker 4: There were plenty of times where I would sit around 155 00:06:51,440 --> 00:06:55,719 Speaker 4: in meetings and literally I would be googling terms, And 156 00:06:55,880 --> 00:06:59,960 Speaker 4: at one meeting, Larry Page actually caught me googling terms 157 00:07:00,400 --> 00:07:02,160 Speaker 4: and he kind of pointed that out to other people 158 00:07:02,160 --> 00:07:04,159 Speaker 4: in the room, which was a little embarrassing. But I 159 00:07:04,160 --> 00:07:06,080 Speaker 4: figured there were some things that I could do that 160 00:07:06,120 --> 00:07:10,080 Speaker 4: they can do, and so it was a learning curve 161 00:07:10,440 --> 00:07:14,400 Speaker 4: and my dad always he taught me at a young age, 162 00:07:15,800 --> 00:07:18,440 Speaker 4: a term that I've used constantly with my teams. He 163 00:07:18,520 --> 00:07:22,120 Speaker 4: said in his lab at Stanford, if a physicist could 164 00:07:22,160 --> 00:07:25,280 Speaker 4: not define a quark in under thirty seconds, they didn't 165 00:07:25,320 --> 00:07:27,400 Speaker 4: know what they were talking about, And so I used 166 00:07:27,400 --> 00:07:29,440 Speaker 4: the quark test all the time. If somebody's rambling on 167 00:07:29,480 --> 00:07:31,160 Speaker 4: and on and they can't get to the point, they 168 00:07:31,200 --> 00:07:32,960 Speaker 4: probably don't know what they're talking about. They failed the 169 00:07:33,000 --> 00:07:35,840 Speaker 4: quart test. My finance team knows this core test, and 170 00:07:35,840 --> 00:07:38,920 Speaker 4: at Google I'm working with amazing computer scientists, so they 171 00:07:38,960 --> 00:07:41,520 Speaker 4: never fail the cork test. They can explain things really clearly, 172 00:07:41,560 --> 00:07:42,880 Speaker 4: which shoots you up the learning curve. 173 00:07:42,920 --> 00:07:44,760 Speaker 1: But did you understand what they were talking about from 174 00:07:44,760 --> 00:07:46,680 Speaker 1: the beginning, or did you have a special tutor that's 175 00:07:46,800 --> 00:07:49,200 Speaker 1: taking technology for deedails I had. 176 00:07:49,080 --> 00:07:51,760 Speaker 4: Actually run tech Banking into Google Public, so I had 177 00:07:51,760 --> 00:07:53,000 Speaker 4: a little sneak preview. 178 00:07:53,040 --> 00:07:56,080 Speaker 1: So today for people who are not experts on Google 179 00:07:56,120 --> 00:07:59,559 Speaker 1: and Google Search, Larry Page really developed the page system 180 00:07:59,600 --> 00:08:02,200 Speaker 1: I guess was called, and it was unique. But when 181 00:08:02,320 --> 00:08:05,120 Speaker 1: he came to get the initial money in Silicon Valley, 182 00:08:05,160 --> 00:08:06,960 Speaker 1: people said, well, there's plenty of search engines out here. 183 00:08:06,960 --> 00:08:09,800 Speaker 1: They're like twelve or thirteen search engine companies, and so 184 00:08:10,280 --> 00:08:12,160 Speaker 1: people didn't think it was anything so unique. 185 00:08:12,160 --> 00:08:13,160 Speaker 2: What turned out to be. 186 00:08:13,160 --> 00:08:16,360 Speaker 1: So unique about the page system that it made Google 187 00:08:16,520 --> 00:08:17,720 Speaker 1: such a powerful company. 188 00:08:17,960 --> 00:08:19,680 Speaker 4: I actually remember those days because I was one of 189 00:08:19,720 --> 00:08:21,480 Speaker 4: the people who said, why do we need It was 190 00:08:21,560 --> 00:08:23,760 Speaker 4: actually the eighth search engine? Why do you need the 191 00:08:23,800 --> 00:08:26,040 Speaker 4: eight search engine? And I was at Morgan Stanley at 192 00:08:26,080 --> 00:08:31,320 Speaker 4: the time nineteen ninety eight running banking, and our research analyst, 193 00:08:31,440 --> 00:08:35,400 Speaker 4: Mary Meeker and iconic analyst, pulled her team together and said, 194 00:08:35,440 --> 00:08:37,600 Speaker 4: you know what, Let's do a test. Let's look at 195 00:08:37,679 --> 00:08:41,080 Speaker 4: all the search engines. Let's do queries and see speed 196 00:08:41,080 --> 00:08:44,480 Speaker 4: and relevance of response. And I think she may have 197 00:08:44,520 --> 00:08:47,440 Speaker 4: started with that eight search engine question as well, but 198 00:08:47,559 --> 00:08:49,000 Speaker 4: it quickly rose to the top. 199 00:08:49,200 --> 00:08:51,480 Speaker 3: And that has been the ethos all along. 200 00:08:51,920 --> 00:08:54,880 Speaker 4: We still to this day have more than one hundred 201 00:08:55,040 --> 00:08:59,400 Speaker 4: product innovations every quarter. The whole idea is continue challenging 202 00:08:59,400 --> 00:09:03,560 Speaker 4: ourselves about how to make the product better, more relevant, faster. 203 00:09:04,040 --> 00:09:07,199 Speaker 4: And what's extraordinary sitting where we are today is how 204 00:09:07,240 --> 00:09:10,160 Speaker 4: searches evolve. So back then it was ten blue links. 205 00:09:10,559 --> 00:09:13,160 Speaker 4: Whoever's old enough in this room to remember ten blue links, 206 00:09:13,559 --> 00:09:14,240 Speaker 4: That's what it was. 207 00:09:14,280 --> 00:09:15,120 Speaker 3: And then it went to. 208 00:09:16,559 --> 00:09:19,680 Speaker 4: Image search, voice search, and now multimodal search. If I 209 00:09:19,720 --> 00:09:22,000 Speaker 4: want your tie, I can take a picture of your tie, 210 00:09:22,440 --> 00:09:25,920 Speaker 4: and then I can just I can lens it, and 211 00:09:25,960 --> 00:09:28,040 Speaker 4: I can find a place to buy your tie. So 212 00:09:28,080 --> 00:09:31,960 Speaker 4: this whole evolution of search just keeps extending the runway 213 00:09:32,000 --> 00:09:32,400 Speaker 4: for a search. 214 00:09:32,400 --> 00:09:34,240 Speaker 3: So it's very different obviously today than it was. 215 00:09:34,559 --> 00:09:36,680 Speaker 1: I suppose I do a Google search on something. Maybe 216 00:09:36,720 --> 00:09:38,760 Speaker 1: I shouldn't be doing a Google search on or. 217 00:09:38,679 --> 00:09:40,240 Speaker 3: Something not that you ever do. 218 00:09:40,320 --> 00:09:43,360 Speaker 1: I wouldn't do that, but I just theoretically can somebody 219 00:09:43,360 --> 00:09:45,720 Speaker 1: from Google, an officer like you look up what I've searched. 220 00:09:46,400 --> 00:09:50,640 Speaker 4: No, you cannot, absolutely, yeah, protected right or protected. 221 00:09:50,559 --> 00:09:51,880 Speaker 2: Even if the government comes along. 222 00:09:54,120 --> 00:09:56,160 Speaker 4: We do not look at what you search. Can go 223 00:09:56,200 --> 00:09:58,559 Speaker 4: into incognitumo, but we do not look at what you search. 224 00:09:58,720 --> 00:09:59,040 Speaker 2: Okay. 225 00:09:59,160 --> 00:10:01,880 Speaker 1: So the company a long time was spelled was called Google, 226 00:10:01,920 --> 00:10:04,640 Speaker 1: and Google used to be spelled differently. Why did they 227 00:10:04,640 --> 00:10:07,160 Speaker 1: spell Google that way as opposed their way it was 228 00:10:07,200 --> 00:10:10,640 Speaker 1: originally spelled, which was e L. Did they not know 229 00:10:10,720 --> 00:10:11,960 Speaker 1: that was spelled differently? 230 00:10:12,480 --> 00:10:13,960 Speaker 3: Well, there are a couple of stories around this. 231 00:10:14,040 --> 00:10:17,280 Speaker 4: So one of the stories that I think is true 232 00:10:17,400 --> 00:10:20,920 Speaker 4: and fun is that one of the early venture checks 233 00:10:21,040 --> 00:10:22,920 Speaker 4: actually wrote it that way, so they went with it. 234 00:10:23,200 --> 00:10:26,000 Speaker 1: Okay, so why did Google is the brand name that's 235 00:10:26,040 --> 00:10:28,000 Speaker 1: working very well, companies making a lot of money and 236 00:10:28,040 --> 00:10:30,720 Speaker 1: so forth, But why did you need to go to alphabet? 237 00:10:30,760 --> 00:10:31,960 Speaker 2: And who came up with that name? 238 00:10:32,960 --> 00:10:37,120 Speaker 4: So Larry and Sergei had a vision about kind of 239 00:10:37,160 --> 00:10:41,160 Speaker 4: the next iteration, and there were a lot of different 240 00:10:41,240 --> 00:10:44,600 Speaker 4: things that they were investing in, the whole spirit of 241 00:10:44,640 --> 00:10:47,080 Speaker 4: which is you want to make sure you're investing for 242 00:10:47,120 --> 00:10:50,480 Speaker 4: long term, investing for the future. And in the earliest days, 243 00:10:50,840 --> 00:10:53,200 Speaker 4: what they did is they created something called X. It 244 00:10:53,240 --> 00:10:56,080 Speaker 4: was the moonshot factory within Google Google X, and it 245 00:10:56,120 --> 00:10:58,319 Speaker 4: gave birth to things like Gmail, I mean made it 246 00:10:58,800 --> 00:11:01,439 Speaker 4: was really relevant for all of the type of innovation 247 00:11:01,480 --> 00:11:04,839 Speaker 4: that came out of Google. And by twenty fifteen, their 248 00:11:04,960 --> 00:11:08,680 Speaker 4: view was, we want to be able to avoid distraction 249 00:11:08,800 --> 00:11:10,520 Speaker 4: on Google. Let Google do what it's going to do 250 00:11:10,679 --> 00:11:14,440 Speaker 4: and create another set of businesses that the founders could 251 00:11:14,440 --> 00:11:17,520 Speaker 4: focus on and really nurture growth outside of it. And 252 00:11:17,559 --> 00:11:19,480 Speaker 4: so the word is you would know better than anyone 253 00:11:19,559 --> 00:11:22,280 Speaker 4: is alphabets, and so you put the two together, and 254 00:11:22,360 --> 00:11:23,040 Speaker 4: that was the goal. 255 00:11:23,520 --> 00:11:24,200 Speaker 2: So it used to be. 256 00:11:24,240 --> 00:11:26,600 Speaker 1: When Google was started, you had what was called twenty 257 00:11:26,679 --> 00:11:29,480 Speaker 1: percent time, So for twenty percent of your time, you 258 00:11:29,480 --> 00:11:29,880 Speaker 1: could do. 259 00:11:29,840 --> 00:11:30,600 Speaker 2: Whatever you wanted. 260 00:11:31,040 --> 00:11:33,040 Speaker 1: Theoretically it might be helpful at a company, but it 261 00:11:33,080 --> 00:11:35,920 Speaker 1: wasn't supposed to be necessarily, so you still have twenty 262 00:11:36,000 --> 00:11:37,440 Speaker 1: percent time or they go away. 263 00:11:37,840 --> 00:11:40,520 Speaker 4: Well, it was actually a little more structured than that. 264 00:11:40,640 --> 00:11:43,120 Speaker 4: The goal was if you had some great engineering idea 265 00:11:43,120 --> 00:11:44,720 Speaker 4: and you wanted to launch a new product, you could 266 00:11:44,720 --> 00:11:45,680 Speaker 4: do it in one of two ways. 267 00:11:45,920 --> 00:11:48,800 Speaker 3: You could leave or you could be told. 268 00:11:48,640 --> 00:11:50,720 Speaker 4: You know what, in twenty percent of your time, why 269 00:11:50,720 --> 00:11:53,080 Speaker 4: don't you go experiment with this and see if. 270 00:11:53,000 --> 00:11:53,600 Speaker 3: You can grow it. 271 00:11:54,040 --> 00:11:58,440 Speaker 4: So rather than having great ideas constantly leaving, the view 272 00:11:58,440 --> 00:12:01,640 Speaker 4: as let's nurture the talent, let's give people these growth opportunities, 273 00:12:01,720 --> 00:12:03,920 Speaker 4: let's give it a go. And so that's what the 274 00:12:03,960 --> 00:12:04,960 Speaker 4: twenty percent time was. 275 00:12:05,160 --> 00:12:08,319 Speaker 1: Any twenty percent time product ever get to the market. 276 00:12:08,880 --> 00:12:12,439 Speaker 4: Well, a Gmail is not an inconsequential billions of users. 277 00:12:12,800 --> 00:12:16,120 Speaker 4: Google Brain came out of that. It's our core part 278 00:12:16,160 --> 00:12:19,440 Speaker 4: of our AI business, and then we've continued to evolve it, 279 00:12:19,520 --> 00:12:21,800 Speaker 4: so it moved over to become ax. 280 00:12:21,840 --> 00:12:22,680 Speaker 3: Weymo came out of it. 281 00:12:22,720 --> 00:12:24,280 Speaker 4: So there's quite quite a bit and quite a bit 282 00:12:24,320 --> 00:12:26,000 Speaker 4: of features and applications. 283 00:12:26,120 --> 00:12:28,559 Speaker 2: Think of waymo. Are we going to have driverless cars 284 00:12:28,559 --> 00:12:29,400 Speaker 2: in our lifetime? 285 00:12:29,800 --> 00:12:32,559 Speaker 4: Well, I welcome everybody to come to San Francisco because 286 00:12:32,559 --> 00:12:35,280 Speaker 4: you can actually hail a way Moo in San Francisco, 287 00:12:35,360 --> 00:12:36,640 Speaker 4: hop in it and get where you want to go. 288 00:12:36,679 --> 00:12:37,640 Speaker 3: And it's pretty remarkable. 289 00:12:37,800 --> 00:12:38,480 Speaker 2: Have you done that? 290 00:12:38,559 --> 00:12:40,640 Speaker 3: Absolutely brilliant safe. 291 00:12:41,040 --> 00:12:43,680 Speaker 4: It's so safe that the most fascinating part is within 292 00:12:43,720 --> 00:12:46,760 Speaker 4: about fifteen seconds people are bored because it's so safe there, 293 00:12:46,760 --> 00:12:47,160 Speaker 4: like they. 294 00:12:47,040 --> 00:12:48,520 Speaker 2: Realize, you know, we don't need a helmet or in 295 00:12:48,559 --> 00:12:49,240 Speaker 2: the nuget's safe? 296 00:12:49,320 --> 00:12:49,440 Speaker 4: Right? 297 00:12:49,480 --> 00:12:52,120 Speaker 3: Do you need a helmet with many drivers on the road. 298 00:12:52,240 --> 00:12:54,400 Speaker 1: So for a young woman that's watching this or a 299 00:12:54,400 --> 00:12:57,440 Speaker 1: young man, and what are the recommendations you'd have to 300 00:12:57,480 --> 00:13:00,320 Speaker 1: get ahead? And the finance world technology we're is it 301 00:13:00,360 --> 00:13:02,760 Speaker 1: be smarter than other people, be nicer than the other people, 302 00:13:03,000 --> 00:13:05,000 Speaker 1: be harder working. 303 00:13:05,000 --> 00:13:07,360 Speaker 2: What is it that takes to be successful? 304 00:13:07,800 --> 00:13:10,680 Speaker 4: Well, there's no substitute for hard work, because the hard 305 00:13:10,720 --> 00:13:13,439 Speaker 4: work actually gets you smarter enough the learning curve faster. 306 00:13:13,600 --> 00:13:16,160 Speaker 4: So most certainly that's one of them. I think the 307 00:13:16,200 --> 00:13:19,520 Speaker 4: other I've already said chart your career work for somebody 308 00:13:19,559 --> 00:13:21,199 Speaker 4: who's going to take a risk on you and give 309 00:13:21,240 --> 00:13:24,120 Speaker 4: you runway. But very importantly, we need to do that 310 00:13:24,200 --> 00:13:26,040 Speaker 4: for someone. So at one point, when I was asked 311 00:13:26,080 --> 00:13:29,800 Speaker 4: to run technology equity capital markets on the equity trading floor, 312 00:13:30,360 --> 00:13:33,680 Speaker 4: a senior partner called me into his office and he said, 313 00:13:33,679 --> 00:13:35,520 Speaker 4: I will be your I will be your air cover. 314 00:13:36,040 --> 00:13:37,520 Speaker 4: All the guys that were going to sell you use 315 00:13:37,559 --> 00:13:39,680 Speaker 4: these military terms. There a lot of military guys, but 316 00:13:39,760 --> 00:13:42,000 Speaker 4: it was a good one. I will be your air cover. 317 00:13:42,400 --> 00:13:44,320 Speaker 4: I think you will soar, but if you stumble, I'm 318 00:13:44,360 --> 00:13:47,320 Speaker 4: here to be your air cover. I think everyone needs 319 00:13:47,360 --> 00:13:49,240 Speaker 4: air cover, and I think we all need to. 320 00:13:49,200 --> 00:13:49,960 Speaker 3: Be air cover. 321 00:13:50,559 --> 00:13:53,600 Speaker 4: And the other is keep learning and keep growing. And 322 00:13:53,640 --> 00:13:56,120 Speaker 4: when you're plateauing, my line was what's my highest and 323 00:13:56,160 --> 00:14:00,000 Speaker 4: best use and don't do it on a specific timeline, 324 00:14:00,360 --> 00:14:03,080 Speaker 4: but keep evolving and if you go to the right people, 325 00:14:03,080 --> 00:14:05,160 Speaker 4: they'll keep opening doors and take those doors. 326 00:14:05,160 --> 00:14:06,280 Speaker 3: And then finally, use your voice. 327 00:14:06,440 --> 00:14:08,440 Speaker 1: You have a challenge that many people would like to 328 00:14:08,480 --> 00:14:10,400 Speaker 1: have but they don't have, which is you've got over 329 00:14:10,440 --> 00:14:14,320 Speaker 1: one hundred billion dollars of cash, and so are you 330 00:14:14,360 --> 00:14:17,000 Speaker 1: going to invest that in private equity firms, or are 331 00:14:17,040 --> 00:14:20,160 Speaker 1: you going to do new technology? What are you going 332 00:14:20,200 --> 00:14:21,880 Speaker 1: to do with one hundred billion dollars more than one 333 00:14:21,920 --> 00:14:25,280 Speaker 1: hundred billion dollars of cash? And you know, have you 334 00:14:25,320 --> 00:14:26,960 Speaker 1: thought about that? You have people coming up to you 335 00:14:27,040 --> 00:14:30,080 Speaker 1: all the time with great ideas for that cash. 336 00:14:30,120 --> 00:14:32,920 Speaker 4: We do as you would imagine. So, look, we're continuing 337 00:14:32,920 --> 00:14:35,040 Speaker 4: to invest in the business. There's a lot of extraordinary 338 00:14:35,160 --> 00:14:38,320 Speaker 4: upside in the business. And then we do make investments 339 00:14:38,360 --> 00:14:41,240 Speaker 4: and acquisitions, so do all of our peers. There's a 340 00:14:41,240 --> 00:14:43,360 Speaker 4: lot that's exciting going on in the world, and so 341 00:14:43,400 --> 00:14:46,400 Speaker 4: we're looking across the board. Starts within the business, then 342 00:14:46,400 --> 00:14:49,800 Speaker 4: it goes to investments and acquisitions, then obviously return to 343 00:14:49,840 --> 00:14:52,960 Speaker 4: capital through a not in consequential share repurchase program. 344 00:14:53,120 --> 00:14:54,840 Speaker 2: Let's talk about artificial intelligence. 345 00:14:55,360 --> 00:14:57,800 Speaker 1: Artificial intelligence has gotten a lot of publicity in the 346 00:14:57,880 --> 00:15:02,280 Speaker 1: last year or so, and open ai has got an 347 00:15:02,400 --> 00:15:05,520 Speaker 1: enormous amount of it, and they have an affiliation with 348 00:15:05,560 --> 00:15:06,720 Speaker 1: another technology company. 349 00:15:06,760 --> 00:15:08,760 Speaker 2: I can't remember the name of it. I've heard that 350 00:15:08,880 --> 00:15:09,440 Speaker 2: another one. 351 00:15:09,600 --> 00:15:12,400 Speaker 1: But do you have your own kind of open ai 352 00:15:12,840 --> 00:15:14,960 Speaker 1: company or do you do it all internally? And what 353 00:15:15,000 --> 00:15:17,200 Speaker 1: do you do to compete with open ai? And this 354 00:15:17,280 --> 00:15:18,480 Speaker 1: other technology company. 355 00:15:19,320 --> 00:15:24,000 Speaker 4: So we've had We've been infusing product at Google with 356 00:15:24,120 --> 00:15:28,080 Speaker 4: AI for more than a decade. In fact, billions of 357 00:15:28,120 --> 00:15:32,400 Speaker 4: people today are benefiting from AI across our products. It's 358 00:15:32,440 --> 00:15:35,880 Speaker 4: benefiting what you see in search, in maps, and commerce 359 00:15:36,040 --> 00:15:40,600 Speaker 4: and YouTube. You know, I just mentioned multimodal search, the 360 00:15:40,640 --> 00:15:43,840 Speaker 4: ability to search with your camera, when you search for 361 00:15:43,960 --> 00:15:48,360 Speaker 4: your kids and photos, that's AI. So AI has continued 362 00:15:48,400 --> 00:15:51,360 Speaker 4: to be a way to enhance what the product experiences. 363 00:15:51,440 --> 00:15:54,200 Speaker 4: And we've done that historically through two groups within Google. 364 00:15:54,200 --> 00:15:56,880 Speaker 4: One Google Brain I already mentioned, and the other is 365 00:15:56,920 --> 00:16:01,640 Speaker 4: deep Mind, an extraordinary acquisition back years ago led by 366 00:16:01,840 --> 00:16:04,880 Speaker 4: an extraordinary entrepreneur, Demesistatus, And we've put the two together 367 00:16:05,440 --> 00:16:09,800 Speaker 4: last year, which has been really exciting. And so we 368 00:16:09,840 --> 00:16:13,880 Speaker 4: are building on that foundation that has been an experience 369 00:16:13,920 --> 00:16:15,080 Speaker 4: for the last decade. 370 00:16:15,240 --> 00:16:18,640 Speaker 1: What's the excitement of work in technology in the Silicon Valley? 371 00:16:18,920 --> 00:16:21,240 Speaker 1: Is it even more exciting than working in finance? Or 372 00:16:21,280 --> 00:16:22,200 Speaker 1: not quite as exciting? 373 00:16:22,200 --> 00:16:25,600 Speaker 3: But okay, it's hard to believe it's more exciting, ed. 374 00:16:26,200 --> 00:16:29,680 Speaker 4: I mean, we're living in the most extraordinary time with AI. 375 00:16:29,760 --> 00:16:33,280 Speaker 4: Bill Gates just said that I completely agree. Engineers who've 376 00:16:33,280 --> 00:16:35,760 Speaker 4: been at Google since inception are saying that this is 377 00:16:35,800 --> 00:16:38,600 Speaker 4: the most exciting time in computer science in our lifetime, 378 00:16:39,000 --> 00:16:42,160 Speaker 4: which always strikes me as profound because Google's done okay, 379 00:16:42,800 --> 00:16:47,520 Speaker 4: And what's extraordinary about it really goes to building on 380 00:16:47,600 --> 00:16:52,600 Speaker 4: this decade of innovative work in AI. And so where 381 00:16:52,600 --> 00:16:53,280 Speaker 4: are we now. 382 00:16:53,440 --> 00:16:56,080 Speaker 3: We're at the What we're doing. 383 00:16:56,200 --> 00:16:59,960 Speaker 4: Is we're addressing some of the most profound social challenge 384 00:17:00,160 --> 00:17:03,720 Speaker 4: is with AI in ways that are transformative. So to 385 00:17:03,720 --> 00:17:06,760 Speaker 4: give you an a couple of examples, I think that 386 00:17:06,800 --> 00:17:08,800 Speaker 4: one of the extraordinary places for all of us, and 387 00:17:08,840 --> 00:17:09,880 Speaker 4: we've heard a lot about it. 388 00:17:09,800 --> 00:17:13,720 Speaker 3: Here over lunch, is healthcare. And part of the reason is. 389 00:17:13,760 --> 00:17:18,240 Speaker 4: It's the ability with AI to aggregate so much data 390 00:17:18,240 --> 00:17:21,919 Speaker 4: that you can actually have a level of diagnosis that 391 00:17:22,000 --> 00:17:25,359 Speaker 4: is better than what specialists can do. So one example 392 00:17:25,640 --> 00:17:29,359 Speaker 4: breast cancer. Back in twenty fifteen, Google had a breakthrough 393 00:17:29,800 --> 00:17:33,639 Speaker 4: in detection early detection of metastatic breast cancer. One in 394 00:17:33,760 --> 00:17:37,040 Speaker 4: seven women will be diagnosed with breast cancer. I was 395 00:17:37,080 --> 00:17:39,920 Speaker 4: one of those. I've had breast cancer twice, so when 396 00:17:39,960 --> 00:17:42,560 Speaker 4: I heard about this, I did the only rational thing. 397 00:17:42,600 --> 00:17:45,240 Speaker 4: I called my oncologist at Memorial Slung Kettering, and I 398 00:17:45,280 --> 00:17:48,959 Speaker 4: said is this really as important as I hope? And 399 00:17:49,000 --> 00:17:53,919 Speaker 4: he said unequivocally, because only with AI can we democratize healthcare. 400 00:17:54,400 --> 00:17:59,240 Speaker 4: It's the only way that oncologists everywhere, radiologists everywhere, all 401 00:17:59,280 --> 00:18:02,080 Speaker 4: of the medical profession has the ability to leverage the 402 00:18:02,200 --> 00:18:06,119 Speaker 4: insight that AI will give you through scans, reviewing a 403 00:18:06,160 --> 00:18:09,439 Speaker 4: million scans. We're doing the same in other forms of cancer. 404 00:18:09,480 --> 00:18:13,600 Speaker 4: We're doing it with something called diabetic retinopathy blindness cause 405 00:18:14,520 --> 00:18:18,760 Speaker 4: through diabetes, which can be prevented if diagnosed early enough. 406 00:18:19,320 --> 00:18:21,240 Speaker 4: And so I think that when you look at the 407 00:18:21,280 --> 00:18:24,640 Speaker 4: impact of a this is what motivates our engineers. We're 408 00:18:24,640 --> 00:18:27,720 Speaker 4: seeing in healthcare, we're seeing in education, We're seeing it. 409 00:18:27,720 --> 00:18:28,639 Speaker 3: With food scarcity. 410 00:18:28,760 --> 00:18:33,119 Speaker 4: You can improve crop yields by looking at pest issues, 411 00:18:33,680 --> 00:18:38,200 Speaker 4: in forming. We're looking at so many different ways that 412 00:18:38,560 --> 00:18:40,919 Speaker 4: AI can make a difference on the most profound issues. 413 00:18:40,920 --> 00:18:42,960 Speaker 4: One last one, because it's you asked, am I excited 414 00:18:42,960 --> 00:18:46,960 Speaker 4: about it? Yes, It's better than even finance, climate change, 415 00:18:47,119 --> 00:18:51,640 Speaker 4: you know, SOS crisis alerts extraordinary. We've seen the impact 416 00:18:51,680 --> 00:18:54,000 Speaker 4: of buyers and flooding, two hundred and fifty million people 417 00:18:54,040 --> 00:18:57,840 Speaker 4: a year affected by flooding. But with AI, we can 418 00:18:57,920 --> 00:19:02,320 Speaker 4: predict and r with seven days. Notice where the waterflows 419 00:19:02,320 --> 00:19:03,960 Speaker 4: will be to get people out of harm's way. So 420 00:19:04,000 --> 00:19:06,840 Speaker 4: this is not science fiction. This is here today. 421 00:19:06,800 --> 00:19:09,280 Speaker 2: On climate change to be realistic about it. 422 00:19:09,320 --> 00:19:11,400 Speaker 1: These are things that you think that AI can really 423 00:19:11,440 --> 00:19:15,080 Speaker 1: make us make more readily, make us able to solve 424 00:19:15,119 --> 00:19:17,520 Speaker 1: climate change. Is at your point you think we can. 425 00:19:17,560 --> 00:19:20,360 Speaker 3: Well, there's both adaptation and mitigation. 426 00:19:21,000 --> 00:19:23,920 Speaker 4: So around climate change we have a whole other set 427 00:19:24,040 --> 00:19:28,280 Speaker 4: of efforts going on. So, for example, one of the 428 00:19:28,320 --> 00:19:32,000 Speaker 4: major sources of emissions is what you see right out 429 00:19:32,000 --> 00:19:34,760 Speaker 4: the window here start stop from cars. We have something 430 00:19:34,800 --> 00:19:37,440 Speaker 4: called Project green Light which streamlines that so you don't 431 00:19:37,560 --> 00:19:40,720 Speaker 4: have the start stops. We have something else that looks 432 00:19:40,760 --> 00:19:45,479 Speaker 4: at planes. Major source of carbon footprint are contrails, what 433 00:19:45,880 --> 00:19:47,920 Speaker 4: many of us think are the beautiful white plumes off 434 00:19:47,920 --> 00:19:51,160 Speaker 4: the back. You can adjust flight patterns and reduce carbon footprint. 435 00:19:51,240 --> 00:19:54,399 Speaker 4: So the short answer is yes, and it's happening today. 436 00:19:54,520 --> 00:19:56,280 Speaker 4: It's not a hope for science fiction. 437 00:19:56,560 --> 00:19:59,080 Speaker 1: You've been public about your breast cancer. You've talked about it, 438 00:19:59,119 --> 00:20:01,359 Speaker 1: written about it, and so worth why did you go 439 00:20:01,440 --> 00:20:04,000 Speaker 1: public about it? Many women say they don't want it 440 00:20:04,040 --> 00:20:06,160 Speaker 1: to be known that they might have breast cancer. Maybe 441 00:20:06,160 --> 00:20:08,200 Speaker 1: that's right or wrong, But why were you so willing 442 00:20:08,200 --> 00:20:09,840 Speaker 1: to be public about it? 443 00:20:09,840 --> 00:20:11,600 Speaker 4: It is a really personal thing. And when I was 444 00:20:11,600 --> 00:20:14,000 Speaker 4: first diagnosed, I didn't want to talk about it. I 445 00:20:14,040 --> 00:20:16,719 Speaker 4: was at a bank one a few women. You know, 446 00:20:16,880 --> 00:20:19,879 Speaker 4: I was bald, and it's like, it's not what you want. 447 00:20:19,760 --> 00:20:20,480 Speaker 3: To talk about. 448 00:20:20,760 --> 00:20:22,800 Speaker 4: But I got to the point where I realized, in 449 00:20:22,840 --> 00:20:24,840 Speaker 4: this day and age, if you get the right care, 450 00:20:25,880 --> 00:20:28,919 Speaker 4: actually these diseases are manageable, and the scariest part is 451 00:20:28,960 --> 00:20:33,119 Speaker 4: not knowing. And so to me, it was important to 452 00:20:33,240 --> 00:20:36,800 Speaker 4: actually make it clear this is manageable, you can. 453 00:20:36,720 --> 00:20:39,639 Speaker 3: Get through it, and to actually be a resource for people. 454 00:20:40,040 --> 00:20:43,240 Speaker 1: So for many women, you're a role model. You have 455 00:20:43,320 --> 00:20:46,520 Speaker 1: a successful career in finance and technology. You were on 456 00:20:46,560 --> 00:20:48,000 Speaker 1: your first husband. 457 00:20:48,280 --> 00:20:52,000 Speaker 2: Right yeah, yeah, and hanging on hanging on right. So 458 00:20:52,119 --> 00:20:55,679 Speaker 2: and you have three kids, and so you've done it all. 459 00:20:55,720 --> 00:20:58,680 Speaker 1: You've had it all your you know, have a successful career, 460 00:20:58,760 --> 00:21:03,360 Speaker 1: successful marriage, healthy, happy kids. Can you tell us something 461 00:21:03,400 --> 00:21:05,800 Speaker 1: that doesn't make us so feel jealous about you? Because 462 00:21:05,800 --> 00:21:09,160 Speaker 1: you're I mean here, you know everybody can't be as 463 00:21:09,160 --> 00:21:11,720 Speaker 1: good as you, So make us feel that everything isn't 464 00:21:11,720 --> 00:21:13,879 Speaker 1: perfect for you? Leaving aside the breast cancer, so that 465 00:21:14,080 --> 00:21:16,320 Speaker 1: everybody else doesn't feel like they're not going to be 466 00:21:16,359 --> 00:21:18,200 Speaker 1: able to live up to your standards. 467 00:21:18,680 --> 00:21:22,720 Speaker 3: Oh man, other than other Thandians. Look, I think that. 468 00:21:23,280 --> 00:21:27,479 Speaker 4: One of the most important lessons I learned early in 469 00:21:27,520 --> 00:21:30,680 Speaker 4: my career. You know, as a woman in banking, there 470 00:21:30,720 --> 00:21:35,160 Speaker 4: weren't many of us. It wasn't the easiest environment. There 471 00:21:35,160 --> 00:21:40,560 Speaker 4: were a lot of men I've now gently decided to 472 00:21:40,600 --> 00:21:44,240 Speaker 4: call blockheads, but you know, they were worse than blockheads, 473 00:21:44,920 --> 00:21:48,879 Speaker 4: and they made it difficult, and you learned to be resilient. 474 00:21:49,200 --> 00:21:51,800 Speaker 4: The one thing is I was going to outlast them, 475 00:21:52,200 --> 00:21:54,280 Speaker 4: and that would be the joy that came from it. 476 00:21:54,640 --> 00:21:56,159 Speaker 3: Unfortunately, there are obviously a lot. 477 00:21:56,000 --> 00:21:59,960 Speaker 4: Of extraordinary men at Morgan Stanley. There weren't enough senior 478 00:22:00,040 --> 00:22:02,239 Speaker 4: women in the day, and there are more now. And 479 00:22:02,280 --> 00:22:05,399 Speaker 4: so I learned to chart my career. I went to 480 00:22:05,440 --> 00:22:07,440 Speaker 4: people who would take a risk on me, and I said, 481 00:22:07,440 --> 00:22:09,960 Speaker 4: what's my highest and best use? And they opened doors 482 00:22:10,440 --> 00:22:13,159 Speaker 4: that I didn't know existed. And to me, that's the 483 00:22:13,200 --> 00:22:16,720 Speaker 4: most important is those hard day's bad lessons. I just 484 00:22:16,840 --> 00:22:19,120 Speaker 4: chalk them up to being lessons, so I don't actually 485 00:22:19,640 --> 00:22:20,480 Speaker 4: record them. 486 00:22:20,520 --> 00:22:23,320 Speaker 1: So what do you do when you're not working on technology, 487 00:22:24,240 --> 00:22:28,320 Speaker 1: being a wife, being a mother, You have a tennis player, 488 00:22:28,359 --> 00:22:30,639 Speaker 1: or you're a golfer. What do you do for relaxation 489 00:22:30,720 --> 00:22:33,960 Speaker 1: the content you have time for relaxation, Well, I. 490 00:22:33,960 --> 00:22:36,560 Speaker 4: Kind of merge things because there's nothing more joyful to 491 00:22:36,560 --> 00:22:38,640 Speaker 4: me than going on hikes with my kids or bike 492 00:22:38,720 --> 00:22:42,560 Speaker 4: rides with my kids, and so it's you. 493 00:22:42,480 --> 00:22:43,320 Speaker 3: Know, it's a lot of that. 494 00:22:43,480 --> 00:22:44,720 Speaker 2: Are your parents alive now? 495 00:22:45,119 --> 00:22:45,520 Speaker 3: They are not? 496 00:22:46,160 --> 00:22:49,280 Speaker 1: And did they live to see your success before they 497 00:22:49,280 --> 00:22:49,840 Speaker 1: passed away? 498 00:22:50,480 --> 00:22:50,960 Speaker 3: They did. 499 00:22:51,240 --> 00:22:53,359 Speaker 4: My mom, actually, when I was a young kid, said 500 00:22:53,680 --> 00:22:56,240 Speaker 4: she was a psychologist, and she said what's really important 501 00:22:56,240 --> 00:22:59,440 Speaker 4: for women is have your own identity and a career 502 00:22:59,440 --> 00:23:00,240 Speaker 4: outside of them home. 503 00:23:00,359 --> 00:23:02,040 Speaker 3: She told me that when I was eight, my little 504 00:23:02,080 --> 00:23:02,800 Speaker 3: sister was six. 505 00:23:02,880 --> 00:23:04,960 Speaker 4: For some reasons, he thought that's the time you need 506 00:23:05,000 --> 00:23:06,560 Speaker 4: to send that message. 507 00:23:06,600 --> 00:23:08,440 Speaker 3: So I'm grateful to her for that message. 508 00:23:08,520 --> 00:23:10,919 Speaker 1: Your father did he ever say this is better than 509 00:23:10,920 --> 00:23:12,200 Speaker 1: being a physicist what you're doing. 510 00:23:13,000 --> 00:23:15,000 Speaker 3: My dad was pretty remarkable, you know. 511 00:23:15,160 --> 00:23:18,880 Speaker 4: The tale end of that story about his journey from 512 00:23:18,920 --> 00:23:21,240 Speaker 4: no high school education to a PhD in a career 513 00:23:21,280 --> 00:23:24,639 Speaker 4: at Stanford is he said education is your passport for 514 00:23:24,720 --> 00:23:28,800 Speaker 4: freedom and so the only point he impressed on us 515 00:23:28,840 --> 00:23:34,480 Speaker 4: over and over was really focus on education, keep opening doors, 516 00:23:34,920 --> 00:23:37,240 Speaker 4: and take risks. If he didn't take the risk he 517 00:23:37,280 --> 00:23:40,600 Speaker 4: took to get himself out of Austria to teach himself physics, 518 00:23:40,960 --> 00:23:42,920 Speaker 4: he wouldn't have made it. And he was so grateful 519 00:23:43,280 --> 00:23:45,640 Speaker 4: to get to the United States. So if there's anything else, 520 00:23:45,720 --> 00:23:48,240 Speaker 4: it was that the life that he never expected he 521 00:23:48,240 --> 00:23:49,600 Speaker 4: would have, and then to have a family. 522 00:23:51,240 --> 00:23:53,760 Speaker 1: Thanks for listening to hear more of my interviews. You 523 00:23:53,800 --> 00:23:57,960 Speaker 1: can subscribe and download my podcast on Spotify, Apple, or 524 00:23:57,960 --> 00:23:58,760 Speaker 1: wherever you listen.