1 00:00:02,440 --> 00:00:06,760 Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. 2 00:00:09,560 --> 00:00:15,040 Speaker 2: This is Master's in Business with Barry Ridholds on Bloomberg Radio. 3 00:00:16,480 --> 00:00:19,639 Speaker 1: This week on the podcast Wow, this is really so 4 00:00:19,760 --> 00:00:23,600 Speaker 1: exciting to share with you. We hosted a conference out 5 00:00:23,640 --> 00:00:27,520 Speaker 1: in Huntington Beach, California, my firm ridhel Schwap Management along 6 00:00:27,560 --> 00:00:32,120 Speaker 1: with Advisor Circle called future Proof. It's a giant event 7 00:00:32,479 --> 00:00:35,199 Speaker 1: on the beach in Huntington Beach, California. 8 00:00:35,920 --> 00:00:36,479 Speaker 3: Part of the. 9 00:00:36,440 --> 00:00:40,880 Speaker 1: Event is a series of panels and interviews. In fireside chats, 10 00:00:41,640 --> 00:00:47,199 Speaker 1: I got to sit down with Pallenteer co founder Joe Lonsdale. 11 00:00:48,120 --> 00:00:52,360 Speaker 1: He's really a fascinating guy. He's been a serial entrepreneur, 12 00:00:53,400 --> 00:00:57,760 Speaker 1: managing money for Peter Thiel, interning initially at a Whole 13 00:00:57,800 --> 00:01:03,880 Speaker 1: Places PayPal, which he then just one successful company after another. 14 00:01:05,040 --> 00:01:08,840 Speaker 1: Just a fascinating guy. So we spoke for about thirty 15 00:01:08,880 --> 00:01:12,399 Speaker 1: thirty five minutes. I thought the conversation was fascinating. We 16 00:01:12,520 --> 00:01:17,880 Speaker 1: talked not only about Pallenteer and the defense industry and 17 00:01:17,959 --> 00:01:21,360 Speaker 1: how the world of warfare is changing. Lonsdale is a 18 00:01:21,440 --> 00:01:25,920 Speaker 1: serial entrepreneur who has had success after success after success, 19 00:01:26,560 --> 00:01:29,440 Speaker 1: and is still a relatively young guy. And there's more 20 00:01:29,520 --> 00:01:31,800 Speaker 1: fascinating things to come from him. 21 00:01:32,240 --> 00:01:32,399 Speaker 3: Here. 22 00:01:32,440 --> 00:01:37,760 Speaker 1: It is my discussion with palenteers Joe Lonsdale in Huntington 23 00:01:37,800 --> 00:01:41,360 Speaker 1: Beach at future Proof twenty twenty four. So I just 24 00:01:41,520 --> 00:01:44,800 Speaker 1: highlighted a handful of things about your career, but I 25 00:01:44,840 --> 00:01:49,440 Speaker 1: really want to delve into the specifics. You're at Stanford 26 00:01:50,120 --> 00:01:54,600 Speaker 1: studying computer science and somehow you land a job as 27 00:01:54,640 --> 00:01:56,760 Speaker 1: an intern at PayPal. 28 00:01:57,120 --> 00:01:58,360 Speaker 3: Tell us a little bit about that. 29 00:01:58,800 --> 00:02:01,480 Speaker 4: Well, this was a pretty cool place. So Elon Musk 30 00:02:01,560 --> 00:02:04,080 Speaker 4: with his smartest friends started the company back then in 31 00:02:04,080 --> 00:02:07,080 Speaker 4: the nineties called X and Peter Thiel and his smartest 32 00:02:07,080 --> 00:02:10,560 Speaker 4: friends started Confinity, and they were two of eight competitors, 33 00:02:10,560 --> 00:02:12,920 Speaker 4: and they decided rather and destroy each other, to merge. 34 00:02:13,040 --> 00:02:15,480 Speaker 4: It was actually interesting times, like people were working so 35 00:02:15,520 --> 00:02:17,560 Speaker 4: hard that some of the people working for Peter at 36 00:02:17,560 --> 00:02:19,760 Speaker 4: one point had not gotten enough sleep and were suggesting 37 00:02:19,800 --> 00:02:21,920 Speaker 4: ways to bomb the office of the other guys. 38 00:02:21,919 --> 00:02:23,200 Speaker 2: They realized this is betterly bad. 39 00:02:23,240 --> 00:02:25,840 Speaker 4: We should probably stop this, and so the companies merged 40 00:02:25,840 --> 00:02:27,840 Speaker 4: a form PayPal, and a lot of the most talented 41 00:02:27,840 --> 00:02:29,960 Speaker 4: people from stan Aford computer science went there. 42 00:02:30,000 --> 00:02:32,080 Speaker 2: At that time. It was amazing place. 43 00:02:32,120 --> 00:02:35,200 Speaker 4: Elon kept trying to rename PayPal back to x dot com, 44 00:02:35,240 --> 00:02:36,720 Speaker 4: which they didn't let him do, so I guess he 45 00:02:36,760 --> 00:02:40,320 Speaker 4: eventually got his way twenty years later with Twitter. But no, 46 00:02:40,680 --> 00:02:42,600 Speaker 4: it was a really fun place to learn and a 47 00:02:42,639 --> 00:02:44,720 Speaker 4: lot of my friends there, these guys were like ten 48 00:02:44,760 --> 00:02:46,960 Speaker 4: or fifteen years older than me. A lot of people 49 00:02:47,000 --> 00:02:48,959 Speaker 4: who were working there ended up going on to start 50 00:02:49,360 --> 00:02:53,880 Speaker 4: YouTube and Yelp and you know, LinkedIn and all sorts 51 00:02:53,919 --> 00:02:54,600 Speaker 4: of great companies. 52 00:02:54,680 --> 00:02:56,400 Speaker 2: So a fun place to learn. 53 00:02:56,320 --> 00:02:58,320 Speaker 3: Right, that was quite a brain trust over there. 54 00:02:58,480 --> 00:03:01,520 Speaker 1: Yeah, your next role is it Peter Teal's hedge fund, 55 00:03:01,639 --> 00:03:06,200 Speaker 1: Clarium Capital. You described that as one of the top 56 00:03:06,480 --> 00:03:09,400 Speaker 1: intellectual think tanks in the world. Tell us a little 57 00:03:09,400 --> 00:03:12,880 Speaker 1: bit about your experience working with Teal at Clarium Capital. 58 00:03:13,840 --> 00:03:14,120 Speaker 2: Yeah. 59 00:03:14,160 --> 00:03:17,320 Speaker 4: Sure, that was a global macro hedge fund, and so 60 00:03:17,800 --> 00:03:20,040 Speaker 4: that's a really fun part of finance where you just 61 00:03:20,040 --> 00:03:21,960 Speaker 4: get to try to figure out at a high level 62 00:03:22,040 --> 00:03:24,960 Speaker 4: what's going on in the world, and lots of arguments 63 00:03:24,960 --> 00:03:28,200 Speaker 4: about politics and economics and history and financial markets, and 64 00:03:28,240 --> 00:03:30,840 Speaker 4: you try to on one hat as quantitative you're modeling 65 00:03:31,280 --> 00:03:33,840 Speaker 4: different things like, you know, the Australian currency versus a 66 00:03:33,840 --> 00:03:37,280 Speaker 4: price of commodities versus you know, what's going on in China, 67 00:03:37,480 --> 00:03:38,960 Speaker 4: and on the other hand, you're kind of just just 68 00:03:39,000 --> 00:03:41,000 Speaker 4: discussing what's going to happen the next five or ten years. 69 00:03:41,000 --> 00:03:43,480 Speaker 4: And we you know, we had a really good ten 70 00:03:43,520 --> 00:03:45,280 Speaker 4: year run. But why I was there. I tried to 71 00:03:45,360 --> 00:03:47,160 Speaker 4: hire a bunch of my smartest friends to help us, 72 00:03:47,200 --> 00:03:49,640 Speaker 4: and they thought finance was boring, and we started a 73 00:03:49,720 --> 00:03:52,960 Speaker 4: project based on how PayPal was going after all the 74 00:03:52,960 --> 00:03:54,800 Speaker 4: bad guys because you know, the child in Russian mafia 75 00:03:54,800 --> 00:03:56,600 Speaker 4: I had been stealing our money at PayPal, and we 76 00:03:56,680 --> 00:04:00,640 Speaker 4: ended up building these investigative tools and create pounder out 77 00:04:00,640 --> 00:04:01,880 Speaker 4: of there. So that's what that's what I ended up 78 00:04:01,880 --> 00:04:02,440 Speaker 4: doing it instead. 79 00:04:02,480 --> 00:04:04,680 Speaker 1: So I just want to put a little flesh on 80 00:04:04,720 --> 00:04:06,560 Speaker 1: the bones. You said you had a pretty good run. 81 00:04:06,960 --> 00:04:09,840 Speaker 1: You ended up with a very nice ten year track record, 82 00:04:09,880 --> 00:04:12,920 Speaker 1: but first two years out of the gate something like 83 00:04:12,960 --> 00:04:15,120 Speaker 1: plus thirty percent and plus fifty percent? 84 00:04:16,000 --> 00:04:17,520 Speaker 3: Am I getting those numbers about right? 85 00:04:18,000 --> 00:04:18,240 Speaker 2: Yeah? 86 00:04:18,360 --> 00:04:20,360 Speaker 4: I mean, if you want to know, this is macrofinance, right, 87 00:04:20,400 --> 00:04:22,560 Speaker 4: So it's a fun area. Like an example of one 88 00:04:22,600 --> 00:04:24,640 Speaker 4: of the best trades we figured out that worked for 89 00:04:24,680 --> 00:04:29,360 Speaker 4: a few years is Greenspan had cut interest rates and 90 00:04:29,400 --> 00:04:32,919 Speaker 4: there is more money than ever before going into the GSS, 91 00:04:33,000 --> 00:04:34,680 Speaker 4: Fanny May and Freddie Mack, and so you had this 92 00:04:34,800 --> 00:04:37,480 Speaker 4: massive amount of money there, and because these guys were 93 00:04:37,480 --> 00:04:40,480 Speaker 4: so big, when they would hedge their mortgage portfolios, it 94 00:04:40,520 --> 00:04:43,360 Speaker 4: would move all the global fixed income. And so what 95 00:04:43,400 --> 00:04:45,240 Speaker 4: happened was, you remember, like late two thousand and two, 96 00:04:45,320 --> 00:04:49,320 Speaker 4: you had like five six percent interest rates and the 97 00:04:49,360 --> 00:04:52,880 Speaker 4: race started to fall, and so people started refinancing their homes. 98 00:04:53,080 --> 00:04:55,279 Speaker 4: And when people start refinancing their homes, the duration of 99 00:04:55,320 --> 00:04:58,440 Speaker 4: mortgages goes down. So in order to balance the durations, 100 00:04:58,480 --> 00:05:01,080 Speaker 4: Fanny Man and Freddie Mack had to buy huge amounts 101 00:05:01,080 --> 00:05:02,960 Speaker 4: of ten year notes, but they about to buy so 102 00:05:03,040 --> 00:05:05,480 Speaker 4: much that actually made their industrates go lower, which led 103 00:05:05,480 --> 00:05:07,440 Speaker 4: to more refinancing, which led to have them having buying more. 104 00:05:07,480 --> 00:05:09,600 Speaker 4: So was this feedback effect, and you're able to measure 105 00:05:09,600 --> 00:05:10,279 Speaker 4: the feedback effect. 106 00:05:10,320 --> 00:05:11,279 Speaker 2: You got down to like one. 107 00:05:11,160 --> 00:05:14,919 Speaker 4: Year duration three percent ten year notes back then, and 108 00:05:14,800 --> 00:05:16,560 Speaker 4: then all of a sudden it was snapped back really 109 00:05:16,600 --> 00:05:18,080 Speaker 4: quick because all the money was seeing the economy. So 110 00:05:18,120 --> 00:05:20,080 Speaker 4: anyway you can kind of mapped this stuff out, figure 111 00:05:20,080 --> 00:05:22,360 Speaker 4: out how to trade fixed income. You know, it's a fun, 112 00:05:22,400 --> 00:05:23,520 Speaker 4: fun environment. 113 00:05:23,360 --> 00:05:25,000 Speaker 3: That that must have been a fun environment. 114 00:05:25,279 --> 00:05:29,400 Speaker 1: So, so you mentioned Palenteer, I have to mention how 115 00:05:29,440 --> 00:05:30,160 Speaker 1: old were you. 116 00:05:30,240 --> 00:05:32,280 Speaker 3: When you were one of the co founders of Palenteer. 117 00:05:32,320 --> 00:05:33,080 Speaker 3: You were a young guy. 118 00:05:33,279 --> 00:05:36,440 Speaker 4: It's twenty one. I'm forty two now, so it's a 119 00:05:36,440 --> 00:05:37,040 Speaker 4: long time ago. 120 00:05:37,400 --> 00:05:41,880 Speaker 1: And since now we're going to talk about Palenteer. Congratulations 121 00:05:41,960 --> 00:05:44,080 Speaker 1: they're entering the S and P five hundred. 122 00:05:44,200 --> 00:05:46,800 Speaker 4: It's an an awesome milestone. 123 00:05:46,360 --> 00:05:48,839 Speaker 3: At twenty one, did you ever imagine something like that. 124 00:05:49,040 --> 00:05:51,520 Speaker 4: Yeah, I was a pretty obnoxious kid, so you know, actually, 125 00:05:51,880 --> 00:05:54,880 Speaker 4: Palenteer it was great. We gave offers, so we were 126 00:05:54,880 --> 00:05:57,320 Speaker 4: known for having the top engineering culture. Peter was investor 127 00:05:57,360 --> 00:06:00,000 Speaker 4: in Facebook at the time, so our competition was Palenter 128 00:06:00,120 --> 00:06:02,480 Speaker 4: and Facebook for the best engineers. And you really had 129 00:06:02,480 --> 00:06:03,919 Speaker 4: to convince these people this is going to be a 130 00:06:03,920 --> 00:06:04,720 Speaker 4: big upside place. 131 00:06:04,760 --> 00:06:06,800 Speaker 2: And so you give them offers, and you give them 132 00:06:06,800 --> 00:06:07,400 Speaker 2: three options. 133 00:06:07,440 --> 00:06:10,839 Speaker 4: They could have a higher salary but less equity, less stock, 134 00:06:11,400 --> 00:06:13,440 Speaker 4: you know, medium, medium, where you have a lower salary 135 00:06:13,440 --> 00:06:14,640 Speaker 4: but more stock, and. 136 00:06:14,600 --> 00:06:16,400 Speaker 2: I draw up on the option for the first two 137 00:06:16,440 --> 00:06:17,000 Speaker 2: hundred people. 138 00:06:17,279 --> 00:06:19,000 Speaker 4: We'd put a table and we'd say, here's how much 139 00:06:19,000 --> 00:06:21,960 Speaker 4: your stock might be worth. If this company's worth half 140 00:06:22,000 --> 00:06:25,080 Speaker 4: a billion dollars or a billion dollars or five billion dollars. 141 00:06:25,120 --> 00:06:27,800 Speaker 4: I got so much shit for including five billion dollars 142 00:06:27,839 --> 00:06:28,839 Speaker 4: as one of the possibilities. 143 00:06:28,880 --> 00:06:30,440 Speaker 2: People are like, this is a ridiculous show. 144 00:06:30,520 --> 00:06:33,440 Speaker 1: And the market cap today it's about eighty two billion now, 145 00:06:33,560 --> 00:06:35,799 Speaker 1: So it worked out for it's a long time. 146 00:06:35,640 --> 00:06:38,359 Speaker 3: But it worked out twenty years. It for eighty billion dollars. 147 00:06:38,360 --> 00:06:39,320 Speaker 3: It's a well worth trade. 148 00:06:39,360 --> 00:06:44,839 Speaker 1: So when the company launches, it's a big data analytics company. 149 00:06:44,880 --> 00:06:50,000 Speaker 1: Today the focus is defense, commercial and government. Was this 150 00:06:50,160 --> 00:06:53,800 Speaker 1: a natural evolution or was there a pivot somewhere alonger No, we. 151 00:06:53,760 --> 00:06:56,039 Speaker 4: Started the company to kill the bad guys. Yeah, let's 152 00:06:56,040 --> 00:06:57,920 Speaker 4: be clear. I don't know they're supposed to say. I 153 00:06:57,920 --> 00:06:59,480 Speaker 4: don't work there anymore, so I can say it now. 154 00:06:59,600 --> 00:07:01,520 Speaker 4: We started company after nine to eleven to kill the 155 00:07:01,520 --> 00:07:03,839 Speaker 4: bad guys and stop attacks. And we ended up helping 156 00:07:03,920 --> 00:07:06,400 Speaker 4: run the targeting systems in forty alted countries and wiping 157 00:07:06,440 --> 00:07:08,320 Speaker 4: out over ten thousand terrorists, including a lot of the 158 00:07:08,320 --> 00:07:09,120 Speaker 4: most important ones. 159 00:07:09,200 --> 00:07:11,320 Speaker 2: So, and it protects celebrities too. But let's get the 160 00:07:11,320 --> 00:07:11,800 Speaker 2: bad guys. 161 00:07:11,920 --> 00:07:16,120 Speaker 4: Yeah, And it turns out the hard data problems you 162 00:07:16,200 --> 00:07:19,440 Speaker 4: solve when you run the infrastructure could be used for 163 00:07:19,440 --> 00:07:21,640 Speaker 4: a lot of other things. You're basically building ontologies of 164 00:07:21,680 --> 00:07:24,800 Speaker 4: information and workflows and organizing all the data the government 165 00:07:24,920 --> 00:07:26,520 Speaker 4: And when we start a palenter, the government at the 166 00:07:26,520 --> 00:07:30,200 Speaker 4: time spent like thirty eight billion dollars gathering data, So 167 00:07:30,360 --> 00:07:32,040 Speaker 4: I don't even know what it spends now, but massive 168 00:07:32,040 --> 00:07:35,400 Speaker 4: amounts of information and tens of thousands of databases. How 169 00:07:35,400 --> 00:07:36,720 Speaker 4: to hell do you make all this stuff talk to 170 00:07:36,720 --> 00:07:39,040 Speaker 4: each other? And so by solving those problems to kind 171 00:07:39,040 --> 00:07:41,480 Speaker 4: of organize that, it turns out you now how the 172 00:07:41,560 --> 00:07:42,040 Speaker 4: data in a. 173 00:07:42,120 --> 00:07:44,560 Speaker 2: Form where AI can be used really easily. 174 00:07:44,600 --> 00:07:47,560 Speaker 4: So today polunteers really caught the AI wave because it 175 00:07:47,680 --> 00:07:49,600 Speaker 4: enables AI workflows no one else can. 176 00:07:50,000 --> 00:07:54,240 Speaker 1: And am I correct in saying During COVID, plunteer helped 177 00:07:54,280 --> 00:07:57,440 Speaker 1: governments figure out how to monitor, how to track, how 178 00:07:57,440 --> 00:08:01,240 Speaker 1: to roll out vaccines. What was Pallenteer's role during the pandemic. 179 00:08:02,240 --> 00:08:04,960 Speaker 4: Yeah, I mean it's it's it's used by the armed 180 00:08:05,000 --> 00:08:07,800 Speaker 4: forces to organize all their logiosis and supplies and everything. 181 00:08:07,840 --> 00:08:09,320 Speaker 2: So it's a very similar problem. 182 00:08:09,960 --> 00:08:12,239 Speaker 4: How do you use all the data coming in about 183 00:08:12,240 --> 00:08:14,720 Speaker 4: how to prioritize things in a pandemic? Because you're coordinating 184 00:08:14,760 --> 00:08:17,560 Speaker 4: just massive numbers of things and production and all sorts 185 00:08:17,600 --> 00:08:19,600 Speaker 4: of stuff. I mean, you have a lot of fortunate 186 00:08:19,640 --> 00:08:21,840 Speaker 4: y funder companies using it to manage all of their 187 00:08:22,160 --> 00:08:22,920 Speaker 4: and optimize all. 188 00:08:22,880 --> 00:08:25,200 Speaker 2: Of their production and distribution. So obviously it works very 189 00:08:25,200 --> 00:08:25,560 Speaker 2: well for that. 190 00:08:25,560 --> 00:08:27,440 Speaker 4: For the pandemic, I think, I think like thirty six 191 00:08:27,520 --> 00:08:29,440 Speaker 4: countries used it for that too, So it's good. 192 00:08:29,720 --> 00:08:33,560 Speaker 1: So it's a proven technology today. What was it like 193 00:08:33,920 --> 00:08:38,880 Speaker 1: getting governments to recognize the value of this in the 194 00:08:38,920 --> 00:08:40,880 Speaker 1: early two thousands, they would distress It. 195 00:08:41,160 --> 00:08:43,920 Speaker 4: Was almost as difficult as it was to get Arias 196 00:08:43,960 --> 00:08:48,520 Speaker 4: to take auta par seriously the first five years. So no, 197 00:08:48,720 --> 00:08:52,520 Speaker 4: it's uh, it's actually very funny. You do you think 198 00:08:52,559 --> 00:08:54,720 Speaker 4: you think after a punteer, we were like, oh, this 199 00:08:54,760 --> 00:08:57,559 Speaker 4: is going to be easy. No, it's it's listen, governments. 200 00:08:58,120 --> 00:09:01,400 Speaker 4: Governments are very funny. They they want to use things 201 00:09:01,400 --> 00:09:03,079 Speaker 4: that are new and innovative, but they want to use 202 00:09:03,120 --> 00:09:05,600 Speaker 4: things that everyone else is already using. So breaking in 203 00:09:05,760 --> 00:09:07,959 Speaker 4: is a very chicken and egg problem. That's very hard. 204 00:09:08,320 --> 00:09:12,040 Speaker 4: It turns out that there's a lot of money in 205 00:09:12,040 --> 00:09:15,920 Speaker 4: the special forces and special operations units who frankly their 206 00:09:15,960 --> 00:09:17,360 Speaker 4: lives are a lot more on the line than almost 207 00:09:17,400 --> 00:09:20,480 Speaker 4: anyone else because they're they're constantly doing really dangerous missions 208 00:09:20,480 --> 00:09:22,120 Speaker 4: around the world, and then they're running a lot of 209 00:09:22,120 --> 00:09:24,560 Speaker 4: the most important things that our armed forces do. And 210 00:09:24,640 --> 00:09:27,760 Speaker 4: those groups have such bold and such confident people that 211 00:09:27,800 --> 00:09:30,760 Speaker 4: we're able to break in work with them, get them 212 00:09:30,760 --> 00:09:32,320 Speaker 4: to prove that it worked, and then that kind of 213 00:09:32,360 --> 00:09:34,360 Speaker 4: set the precedent for other parts of government to then 214 00:09:34,360 --> 00:09:34,800 Speaker 4: work with us. 215 00:09:34,800 --> 00:09:36,760 Speaker 2: So thank thank goodness for our special obsc groups. 216 00:09:36,880 --> 00:09:39,600 Speaker 1: So wasn't DARPA that first started with you or would 217 00:09:39,600 --> 00:09:40,800 Speaker 1: did you have any work with them? 218 00:09:41,280 --> 00:09:43,200 Speaker 4: I think DARPA was helpful a little bit, but it 219 00:09:43,240 --> 00:09:45,599 Speaker 4: really the thing that really matters is people using it 220 00:09:45,679 --> 00:09:47,959 Speaker 4: on the ground where lives are on the line. You want, 221 00:09:48,000 --> 00:09:49,679 Speaker 4: if you have something that's the best you want to 222 00:09:50,559 --> 00:09:52,920 Speaker 4: it's going to break in because people need it because 223 00:09:52,920 --> 00:09:55,360 Speaker 4: there because something something is existential where they're going to 224 00:09:55,440 --> 00:09:56,679 Speaker 4: die if they don't have it. They're not gonna be 225 00:09:56,679 --> 00:09:57,960 Speaker 4: able to the mission if they don't have it. So 226 00:09:58,240 --> 00:10:00,760 Speaker 4: DARPA is more of an academic thing. That's smart, but 227 00:10:00,800 --> 00:10:02,679 Speaker 4: I'd much rather work with the people whose lives are 228 00:10:02,720 --> 00:10:04,440 Speaker 4: on the line, and that that's how you really break 229 00:10:04,480 --> 00:10:06,120 Speaker 4: in with the best things you. 230 00:10:06,120 --> 00:10:09,160 Speaker 3: Mentioned at a par and Ai. 231 00:10:09,559 --> 00:10:12,120 Speaker 1: Just so you know, chat GBT is what told me 232 00:10:12,160 --> 00:10:13,760 Speaker 1: it was five trillion dollars. 233 00:10:14,000 --> 00:10:16,120 Speaker 2: Well, nachieven, chat GBT is behind. 234 00:10:16,679 --> 00:10:20,400 Speaker 1: So so you found the company in two thousand and nine. 235 00:10:20,480 --> 00:10:21,680 Speaker 3: Today you're the chairman. 236 00:10:22,160 --> 00:10:26,239 Speaker 1: It began life as a cloud based software platform specializing 237 00:10:26,280 --> 00:10:31,280 Speaker 1: in data aggregation, analytics, and reporting of portfolios. 238 00:10:32,000 --> 00:10:33,840 Speaker 3: What was the original business model? 239 00:10:34,160 --> 00:10:37,040 Speaker 4: Well, you know, I had my family office at first, 240 00:10:37,200 --> 00:10:39,120 Speaker 4: right around then it was a smaller family office, and 241 00:10:39,120 --> 00:10:41,280 Speaker 4: then I had a lot of friends and people I 242 00:10:41,400 --> 00:10:44,400 Speaker 4: talked to who ran family offices, who ran rias. There 243 00:10:44,400 --> 00:10:47,080 Speaker 4: were new groups on the West Coast like Iconic and 244 00:10:47,120 --> 00:10:50,520 Speaker 4: others building these firms around the tech world on raa Land, 245 00:10:51,120 --> 00:10:54,680 Speaker 4: and everyone hated their software. And I looked at it 246 00:10:54,720 --> 00:10:56,320 Speaker 4: and it was like, this is a mess, and there's 247 00:10:56,360 --> 00:10:58,360 Speaker 4: not a really good solution here. And you know, we 248 00:10:58,360 --> 00:11:00,400 Speaker 4: were mapping out there's a lot of new possibility thanks 249 00:11:00,440 --> 00:11:02,080 Speaker 4: to the cloud, thanks to what you could do with data. 250 00:11:02,120 --> 00:11:04,800 Speaker 4: So we said, let's build something that's better. And I 251 00:11:04,920 --> 00:11:07,240 Speaker 4: naively thought we would have something that was significantly better 252 00:11:07,240 --> 00:11:09,439 Speaker 4: within a year or two. It turned out it took 253 00:11:09,480 --> 00:11:11,920 Speaker 4: us hundreds of millions of dollars in several years. But 254 00:11:11,960 --> 00:11:13,680 Speaker 4: I am quite confidence the best at this point. 255 00:11:14,000 --> 00:11:16,680 Speaker 1: So the genesis was, Hey, I have to manage my 256 00:11:16,760 --> 00:11:19,880 Speaker 1: own capital and the tools aren't good, I'm going to 257 00:11:20,000 --> 00:11:22,560 Speaker 1: create it. Or was the original plan. I have an 258 00:11:22,600 --> 00:11:24,120 Speaker 1: idea and everybody should be using it. 259 00:11:23,880 --> 00:11:26,880 Speaker 4: It was a business I think in general, in general, 260 00:11:26,880 --> 00:11:29,560 Speaker 4: when you have like some area that you realize is 261 00:11:29,559 --> 00:11:32,040 Speaker 4: broken for you and for people you know, rather than 262 00:11:32,040 --> 00:11:33,679 Speaker 4: just build it for yourself, I think it's like it's 263 00:11:33,679 --> 00:11:35,319 Speaker 4: a good excuse to build a business around it. So 264 00:11:35,440 --> 00:11:37,680 Speaker 4: I was actually CEO full time for a few years 265 00:11:37,720 --> 00:11:40,240 Speaker 4: getting us off the ground. Eric Poryer, who's running for 266 00:11:40,320 --> 00:11:42,560 Speaker 4: over ten years now, is a much better CEO than me. 267 00:11:42,600 --> 00:11:44,640 Speaker 4: So I'm a proud chairman now. But no, we built 268 00:11:44,679 --> 00:11:47,760 Speaker 4: it as a business. I mean, listen, you guys. When 269 00:11:47,760 --> 00:11:50,080 Speaker 4: we first took there's seven thousand custodians in the US, 270 00:11:50,240 --> 00:11:52,720 Speaker 4: and so we first hooked up data. The biggest custodians 271 00:11:52,760 --> 00:11:55,720 Speaker 4: are people like Fidelity and Schwab and others. And we 272 00:11:55,760 --> 00:11:57,280 Speaker 4: get this all set up. We spent, like you know, 273 00:11:57,320 --> 00:11:59,360 Speaker 4: a bunch of time on the first year. We hook 274 00:11:59,440 --> 00:12:01,840 Speaker 4: up the live day we're getting going and it's all wrong. 275 00:12:02,360 --> 00:12:04,240 Speaker 4: They're like, oh, what do we do wrong? And you know, 276 00:12:04,280 --> 00:12:06,920 Speaker 4: and it turns out even those custodians just how bad 277 00:12:07,000 --> 00:12:09,560 Speaker 4: data this is. The space is a message that shows 278 00:12:09,559 --> 00:12:11,760 Speaker 4: out there's lots of hard problems to solve to make 279 00:12:11,800 --> 00:12:13,720 Speaker 4: this stuff all work right together. So it's it is 280 00:12:14,000 --> 00:12:17,160 Speaker 4: and everyone wants to customizing differently. Every ria has their 281 00:12:17,200 --> 00:12:19,480 Speaker 4: own way of doing things, their own way of showing things, 282 00:12:19,520 --> 00:12:20,760 Speaker 4: and so which it. 283 00:12:20,679 --> 00:12:22,360 Speaker 2: Turned out it took us several more years to get 284 00:12:22,360 --> 00:12:22,679 Speaker 2: it right. 285 00:12:22,960 --> 00:12:26,319 Speaker 1: So so seven trillion dollars, you have some very large 286 00:12:26,440 --> 00:12:29,520 Speaker 1: rias on it, you have broker dealers like Morgan standing 287 00:12:29,600 --> 00:12:32,719 Speaker 1: on it. How big can at a par scale? 288 00:12:33,200 --> 00:12:36,320 Speaker 4: Well, I think there's about two hundred and fifty trillion 289 00:12:36,360 --> 00:12:39,000 Speaker 4: dollars globally that's addressable. Maybe only one hundred and fifty to 290 00:12:39,040 --> 00:12:41,840 Speaker 4: two hundred of that would use a resolution. So even 291 00:12:41,840 --> 00:12:43,720 Speaker 4: though we're going really quickly now I think we're growing 292 00:12:43,840 --> 00:12:46,600 Speaker 4: like over thirty percent a year, still are still probably 293 00:12:46,600 --> 00:12:48,720 Speaker 4: at least an our decade of fast growth. 294 00:12:48,800 --> 00:12:50,880 Speaker 2: I mean, this is a giant market, and you know, 295 00:12:50,880 --> 00:12:51,600 Speaker 2: we're still learning. 296 00:12:51,600 --> 00:12:53,800 Speaker 4: I think I think they're still learning every every week 297 00:12:53,800 --> 00:12:56,360 Speaker 4: from clients about how to serve them better. There's there's 298 00:12:56,480 --> 00:12:58,599 Speaker 4: I think about twelve hundred firms or so give or 299 00:12:58,640 --> 00:13:01,040 Speaker 4: take on the platform now, and and you know, I'd 300 00:13:01,040 --> 00:13:03,080 Speaker 4: love to see them triple out over the next over 301 00:13:03,120 --> 00:13:04,280 Speaker 4: the next few years. 302 00:13:04,679 --> 00:13:07,160 Speaker 1: So the most of what out of part focuses on 303 00:13:07,200 --> 00:13:11,520 Speaker 1: our private our public markets, stops, bonds, mutual funds, ETFs. 304 00:13:11,960 --> 00:13:15,160 Speaker 1: But you also said, hey, this private market thingy is 305 00:13:15,160 --> 00:13:16,200 Speaker 1: going to get big one day. 306 00:13:16,360 --> 00:13:18,800 Speaker 4: Well, being able to report on every possible thing someone 307 00:13:18,840 --> 00:13:20,280 Speaker 4: owns its key for out of part, but out of 308 00:13:20,280 --> 00:13:22,400 Speaker 4: by out of part itself doesn't help people access the 309 00:13:22,400 --> 00:13:23,040 Speaker 4: private markets. 310 00:13:23,280 --> 00:13:27,560 Speaker 1: So let's talk a little bit about opto and that platform. 311 00:13:27,760 --> 00:13:31,360 Speaker 1: The idea behind opto and your chairman of Opto Investments 312 00:13:31,760 --> 00:13:34,720 Speaker 1: is to focus on private markets. Tell us what you 313 00:13:34,760 --> 00:13:38,320 Speaker 1: see in that space. Well, what I saw is that 314 00:13:38,480 --> 00:13:40,000 Speaker 1: the way people tend to come to you. 315 00:13:40,080 --> 00:13:41,960 Speaker 4: So so obviously I run an investment firm, A lot 316 00:13:41,960 --> 00:13:43,480 Speaker 4: of my friends run investment firms, have a lot of 317 00:13:43,520 --> 00:13:46,280 Speaker 4: strong opinions about private markets, right, and this is this 318 00:13:46,320 --> 00:13:49,120 Speaker 4: is an area where in the nineteen nineties there is 319 00:13:49,200 --> 00:13:51,120 Speaker 4: a lot more public companies. There's a small number of 320 00:13:51,160 --> 00:13:55,160 Speaker 4: private companies today, you have more private companies and public companies, 321 00:13:55,200 --> 00:13:57,679 Speaker 4: and frankly, a lot of my smartest friends, people doing 322 00:13:57,760 --> 00:14:00,439 Speaker 4: things that are changing how the world works, are mostly 323 00:14:00,480 --> 00:14:03,120 Speaker 4: doing that within private companies. And so today, if you're 324 00:14:03,120 --> 00:14:06,480 Speaker 4: not accessing private markets, you're going to get left way 325 00:14:06,520 --> 00:14:09,040 Speaker 4: behind your returns. I think, especially the next ten years, 326 00:14:09,440 --> 00:14:12,960 Speaker 4: given how AI is changing productivity in so many parts 327 00:14:12,960 --> 00:14:15,440 Speaker 4: of our economy, we could talk about it's very clear 328 00:14:15,480 --> 00:14:17,920 Speaker 4: you get left behind, and that it's messed up that 329 00:14:18,200 --> 00:14:20,080 Speaker 4: a lot of people don't have access to what's clearly 330 00:14:20,080 --> 00:14:22,800 Speaker 4: the higher returning areas if if they're done right. And 331 00:14:22,840 --> 00:14:24,800 Speaker 4: what I saw is the way people were trying to 332 00:14:24,880 --> 00:14:28,440 Speaker 4: sell people on private market stuff is basically purely a 333 00:14:28,480 --> 00:14:30,520 Speaker 4: brokerage model where they come to your firm and they say, 334 00:14:30,520 --> 00:14:33,120 Speaker 4: we're going to make money by selling you kind of 335 00:14:33,120 --> 00:14:36,400 Speaker 4: mediocre crap. That's how a lot of these things operate. 336 00:14:36,440 --> 00:14:39,400 Speaker 4: And I think that's actually frankly discussing it's not it's 337 00:14:39,440 --> 00:14:41,240 Speaker 4: just not. It's just misaligned, Like it's not how any 338 00:14:41,280 --> 00:14:43,560 Speaker 4: of us would do business normally. Is that you you 339 00:14:43,600 --> 00:14:45,400 Speaker 4: don't want to put money into the things that you're 340 00:14:45,400 --> 00:14:47,280 Speaker 4: getting paid to put money in, so you want to 341 00:14:47,640 --> 00:14:49,160 Speaker 4: you want to have an aligned model where we all 342 00:14:49,200 --> 00:14:51,680 Speaker 4: make money together by accessing the best things. And private 343 00:14:51,720 --> 00:14:54,920 Speaker 4: market is especially venture capital, but frankly, certain parts of PE, 344 00:14:55,080 --> 00:14:57,920 Speaker 4: certain parts of all credit, all these other things, they 345 00:14:57,960 --> 00:14:59,880 Speaker 4: have a very high disparity. You really want to get 346 00:15:00,080 --> 00:15:02,960 Speaker 4: in the top decile, top quartile stuff and you're gonna 347 00:15:03,000 --> 00:15:05,080 Speaker 4: do great and if you get into mediocre stuff, you're 348 00:15:05,120 --> 00:15:07,800 Speaker 4: gonna have mediocre results. And so so just the whole 349 00:15:07,800 --> 00:15:10,200 Speaker 4: spaces seemed misaligned to me. And then on top of that, 350 00:15:10,800 --> 00:15:12,920 Speaker 4: it's really stressful for a lot of people to get 351 00:15:12,960 --> 00:15:14,840 Speaker 4: all their clients into these things because they're just lots 352 00:15:14,880 --> 00:15:19,080 Speaker 4: more paperwork, lots of messes, lots of legal stuff, and like, 353 00:15:19,120 --> 00:15:21,920 Speaker 4: why not make it as close as possible to doing 354 00:15:21,920 --> 00:15:24,240 Speaker 4: something in the public markets to do something in private markets? 355 00:15:24,360 --> 00:15:26,920 Speaker 4: And really technology and AI can solve that. So opto 356 00:15:27,120 --> 00:15:30,240 Speaker 4: it's about making people aligned is having one platform. 357 00:15:29,960 --> 00:15:30,800 Speaker 2: Where you do everything. 358 00:15:30,840 --> 00:15:33,040 Speaker 4: And frankly, it's about using my network and my friends 359 00:15:33,120 --> 00:15:35,480 Speaker 4: networks to put what we think is the very best 360 00:15:35,480 --> 00:15:37,000 Speaker 4: stuff on it that my family office is doing, and 361 00:15:37,080 --> 00:15:38,120 Speaker 4: let's share that with others. 362 00:15:38,640 --> 00:15:42,480 Speaker 1: So at this event, we have over two thousand rias 363 00:15:44,200 --> 00:15:48,040 Speaker 1: of these some of them are single practice, small small operations. 364 00:15:48,040 --> 00:15:51,360 Speaker 1: Some are really big firms with tens of billions, hundreds 365 00:15:51,360 --> 00:15:55,680 Speaker 1: of billions of dollars on them. How can large and 366 00:15:55,680 --> 00:15:59,000 Speaker 1: small firms integrate opto into their practice? 367 00:15:59,120 --> 00:15:59,960 Speaker 2: Yeah, I mean they go. 368 00:16:00,200 --> 00:16:03,200 Speaker 4: There are both lots of small firms and some very 369 00:16:03,280 --> 00:16:04,640 Speaker 4: large firms now on opto. 370 00:16:04,720 --> 00:16:06,400 Speaker 2: The goals that it makes it as. 371 00:16:06,240 --> 00:16:09,400 Speaker 4: Easy as possible, similar to Adapar, which has obviously been 372 00:16:09,440 --> 00:16:11,800 Speaker 4: around longer and as a giant, giant company. Now, I mean, 373 00:16:11,880 --> 00:16:13,840 Speaker 4: opto is growing very quickly and we want to learn 374 00:16:14,080 --> 00:16:16,760 Speaker 4: from rias like what about this could be easier for 375 00:16:17,080 --> 00:16:19,480 Speaker 4: you to use it? But we have dozens of firms 376 00:16:19,480 --> 00:16:22,040 Speaker 4: that have that have created custom funds on it for 377 00:16:22,160 --> 00:16:24,440 Speaker 4: their clients and access things that I think otherwise they 378 00:16:24,440 --> 00:16:26,560 Speaker 4: never would have accessed, and made it really easy for 379 00:16:26,600 --> 00:16:27,040 Speaker 4: them to do it. 380 00:16:27,080 --> 00:16:29,240 Speaker 2: So I would love people's feedback on what we're doing. 381 00:16:29,240 --> 00:16:31,920 Speaker 4: Here is a younger company but growing really fast, and 382 00:16:32,040 --> 00:16:34,160 Speaker 4: I'm really proud to kind of get people the best 383 00:16:34,200 --> 00:16:36,200 Speaker 4: access in the alt world. I think it's such a fun, 384 00:16:36,200 --> 00:16:38,480 Speaker 4: interesting world that a lot of people don't know how 385 00:16:38,520 --> 00:16:40,520 Speaker 4: to approach if they know, if they haven't been doing 386 00:16:40,560 --> 00:16:42,160 Speaker 4: it in the past, or if they have been doing 387 00:16:42,240 --> 00:16:44,840 Speaker 4: some but maybe they would have certain expertise in other areas. 388 00:16:44,840 --> 00:16:47,440 Speaker 4: Sometimes for our custom funds, like they'll choose certain areas, 389 00:16:47,640 --> 00:16:50,040 Speaker 4: certain managers they know, but they will compliment it and 390 00:16:50,080 --> 00:16:51,880 Speaker 4: help them do that with other areas they haven't studied 391 00:16:51,880 --> 00:16:52,320 Speaker 4: as much. 392 00:16:52,560 --> 00:16:54,600 Speaker 2: And so you know, we'll love people's feedback. 393 00:16:54,840 --> 00:16:57,040 Speaker 1: So you wear a lot of hats, you're chairmen of 394 00:16:57,080 --> 00:17:00,680 Speaker 1: out of par you're deeply involved in, opto tell us 395 00:17:00,720 --> 00:17:01,800 Speaker 1: about your day job. 396 00:17:01,920 --> 00:17:04,359 Speaker 3: Eight VC a venture capital front. 397 00:17:04,920 --> 00:17:05,960 Speaker 2: Yeah, I know. At the end of the day, I 398 00:17:05,960 --> 00:17:06,600 Speaker 2: went an entrepreneur. 399 00:17:06,640 --> 00:17:08,920 Speaker 4: I like to build things, and a lot of a 400 00:17:08,960 --> 00:17:12,960 Speaker 4: lot of the people from from palent here from Adapar 401 00:17:13,359 --> 00:17:15,840 Speaker 4: have gone on to build a build lots of other companies, 402 00:17:16,119 --> 00:17:18,040 Speaker 4: and so I've been coaching. I started coaching a lot 403 00:17:18,080 --> 00:17:20,800 Speaker 4: of them, just like with PayPal, where we had sixteen 404 00:17:20,800 --> 00:17:23,040 Speaker 4: billion dollar companies come out of that. After eBay bought us, 405 00:17:23,440 --> 00:17:26,560 Speaker 4: Palenteers now had over one hundred successful companies come out 406 00:17:26,560 --> 00:17:28,840 Speaker 4: of it that people have started over the last couple 407 00:17:28,840 --> 00:17:31,359 Speaker 4: of decades. And and so you know, I ended up 408 00:17:31,480 --> 00:17:33,080 Speaker 4: ended up saying, you know, it makes sense to actually 409 00:17:33,080 --> 00:17:35,119 Speaker 4: build an investment firm. My mentors told me I basically 410 00:17:35,160 --> 00:17:37,480 Speaker 4: was doing an investment firm. Didn't have enough money, enough people, 411 00:17:37,880 --> 00:17:39,719 Speaker 4: so so we so the last twelve years we put 412 00:17:39,760 --> 00:17:41,879 Speaker 4: together a pretty big firm in the venture capital space. 413 00:17:42,200 --> 00:17:45,240 Speaker 4: We build, we build and launch companies. We back companies early, 414 00:17:45,280 --> 00:17:49,280 Speaker 4: and I mean we're not Yeah, it's nice and venture 415 00:17:49,320 --> 00:17:51,880 Speaker 4: If you don't raise big funds, they become very, very oversubscribed. 416 00:17:51,920 --> 00:17:53,639 Speaker 4: So I'm not here to raise money for AIGHTVC. But 417 00:17:53,680 --> 00:17:55,520 Speaker 4: it's a it's a fun area. And I'll tell you 418 00:17:55,560 --> 00:17:57,919 Speaker 4: since you're asking about there, there's really two areas that 419 00:17:57,960 --> 00:18:00,639 Speaker 4: we're probably really well known for the last few years. 420 00:18:01,080 --> 00:18:01,959 Speaker 2: One of them is defense. 421 00:18:02,000 --> 00:18:05,440 Speaker 4: We've started multiple new defense companies, including nearby here. We 422 00:18:05,680 --> 00:18:08,520 Speaker 4: actually backed early ANDROL with Palmer Lucky and so my 423 00:18:08,560 --> 00:18:11,520 Speaker 4: expounder colleagues, and they're become a new defense prime, which 424 00:18:11,520 --> 00:18:13,119 Speaker 4: is really cool. If you haven't checked it out online, 425 00:18:13,119 --> 00:18:15,439 Speaker 4: there's amazing videos of the things they're doing. And then 426 00:18:15,440 --> 00:18:17,720 Speaker 4: the other the other two one of them, you know, 427 00:18:17,800 --> 00:18:19,840 Speaker 4: drone swarms have become a huge problem. 428 00:18:20,520 --> 00:18:21,840 Speaker 2: This is really hard to stop. 429 00:18:21,880 --> 00:18:23,920 Speaker 4: We're spending two million dollars missiles to shoot down cheap 430 00:18:23,920 --> 00:18:26,000 Speaker 4: little drones with bombs coming in our troops and they'll 431 00:18:26,000 --> 00:18:28,760 Speaker 4: swarm one hundred at once. So we figured out how 432 00:18:28,760 --> 00:18:32,720 Speaker 4: to use new technology to send out microwave radiation really 433 00:18:32,720 --> 00:18:35,760 Speaker 4: really far from pretty small, pretty small device to shoot 434 00:18:35,760 --> 00:18:38,639 Speaker 4: down swarms of drones, and we're now deployed live. It 435 00:18:39,119 --> 00:18:40,960 Speaker 4: turns out the AI chips can get the power to 436 00:18:41,000 --> 00:18:42,920 Speaker 4: hit the guy. You might try tomitter all at once 437 00:18:42,960 --> 00:18:44,760 Speaker 4: turn them off. So we build that, and we have 438 00:18:44,840 --> 00:18:48,320 Speaker 4: another company building thousands of ships for the US Navy, 439 00:18:48,359 --> 00:18:50,400 Speaker 4: smaller ships because it turns out China has two hundred 440 00:18:50,400 --> 00:18:53,280 Speaker 4: times our shipbuilding capacity, which is frankly a huge crisis. 441 00:18:53,320 --> 00:18:54,920 Speaker 4: You know, it used to being World War Two, Germans 442 00:18:54,920 --> 00:18:56,639 Speaker 4: had better ships than we did, but every time we 443 00:18:56,720 --> 00:18:58,280 Speaker 4: lose a ship, you'd build three morecs. We have the 444 00:18:58,320 --> 00:19:01,600 Speaker 4: best building capacity America now with with literally two hundred 445 00:19:01,600 --> 00:19:04,240 Speaker 4: times the ship building capacity in China, very scary for 446 00:19:04,240 --> 00:19:06,399 Speaker 4: our ability to turn them. So we're figuring out how 447 00:19:06,400 --> 00:19:09,240 Speaker 4: to take our best and brightest. Frankly, Elon Musk's Who's 448 00:19:09,240 --> 00:19:13,040 Speaker 4: a Good Friend has like really revitalized advanced manufacturing in America. 449 00:19:13,200 --> 00:19:15,680 Speaker 4: We're taking some of that talent putting it into military 450 00:19:15,720 --> 00:19:17,200 Speaker 4: areas as well to make sure we stay ahead. 451 00:19:17,200 --> 00:19:18,480 Speaker 2: Of the bad guys. So so wors we're doing a 452 00:19:18,480 --> 00:19:19,080 Speaker 2: lot of defense. 453 00:19:19,400 --> 00:19:21,520 Speaker 4: And then the one one other area I'll mention is 454 00:19:21,520 --> 00:19:24,160 Speaker 4: what we call AI services. And so there's a huge 455 00:19:24,200 --> 00:19:26,680 Speaker 4: part of our economy right now that we can we've 456 00:19:26,720 --> 00:19:30,440 Speaker 4: showing we can actually double or triple a productivity using AI. 457 00:19:30,680 --> 00:19:34,320 Speaker 4: And so this is this is this is stuff like healthcare, building, logistics, 458 00:19:34,320 --> 00:19:35,840 Speaker 4: building back office processes. 459 00:19:36,040 --> 00:19:38,159 Speaker 2: In the alts world, it's like how do you know, 460 00:19:38,160 --> 00:19:40,080 Speaker 2: how do you manage and subscribe and deal with all 461 00:19:40,119 --> 00:19:41,320 Speaker 2: the al paperwork and stuff. 462 00:19:41,320 --> 00:19:43,919 Speaker 4: There's just lots of these areas that are gonna just 463 00:19:43,960 --> 00:19:46,200 Speaker 4: be completely changed, and so we think there's multi trilion 464 00:19:46,240 --> 00:19:48,480 Speaker 4: dollar opportunities in those areas and building a lot of 465 00:19:48,480 --> 00:19:49,720 Speaker 4: companies that are succeeding in them. 466 00:19:50,000 --> 00:19:52,160 Speaker 1: I want to stay with defense a little bit because 467 00:19:52,280 --> 00:19:55,800 Speaker 1: you're involved in so many really interesting areas. I first 468 00:19:55,840 --> 00:19:58,679 Speaker 1: heard of Palmer Lucky with the Oculus, which you were 469 00:19:58,680 --> 00:20:01,840 Speaker 1: an early investor in before I think Facebook ended up 470 00:20:01,840 --> 00:20:02,880 Speaker 1: buying buying that. 471 00:20:03,320 --> 00:20:05,680 Speaker 4: Yeah, Facebook bought up for over two billion dollars just 472 00:20:05,720 --> 00:20:07,159 Speaker 4: a few years. Then you made an ability here at 473 00:20:07,200 --> 00:20:08,720 Speaker 4: like twenty two or something, which is go go to 474 00:20:08,720 --> 00:20:09,600 Speaker 4: your head pretty fast. 475 00:20:09,880 --> 00:20:12,600 Speaker 1: And then not too long ago, maybe it was Wired 476 00:20:12,640 --> 00:20:16,960 Speaker 1: magazine did a profile on really interesting things that Palmer 477 00:20:17,040 --> 00:20:21,080 Speaker 1: is doing with drone technology and defense technology. 478 00:20:21,400 --> 00:20:23,040 Speaker 3: Tell us a little bit about what's going on in 479 00:20:23,040 --> 00:20:23,520 Speaker 3: that space. 480 00:20:23,840 --> 00:20:24,040 Speaker 2: Yeah. 481 00:20:24,080 --> 00:20:28,680 Speaker 4: So, basically, Pounteer in SpaceX were the first two companies 482 00:20:28,680 --> 00:20:31,399 Speaker 4: to break in and effectively become some form of defense prime, 483 00:20:32,040 --> 00:20:33,880 Speaker 4: the first new ones in thirty years because we had 484 00:20:34,040 --> 00:20:36,320 Speaker 4: we had all these old primes, they all consolidated after 485 00:20:36,320 --> 00:20:38,280 Speaker 4: the Cold were end in the nineties, and they basically 486 00:20:38,280 --> 00:20:41,120 Speaker 4: had a total lock on DC and Poundeer. It took 487 00:20:41,160 --> 00:20:43,680 Speaker 4: us a long time, a lot of stubbornness to break 488 00:20:43,720 --> 00:20:47,480 Speaker 4: in and and you know, some points we had to 489 00:20:47,480 --> 00:20:49,560 Speaker 4: sue the US government because they were doing crazy things 490 00:20:49,600 --> 00:20:51,800 Speaker 4: that we want. SpaceX similarly had to sue the US 491 00:20:51,880 --> 00:20:54,600 Speaker 4: government because they just discriminated against new things, right, and 492 00:20:54,600 --> 00:20:56,960 Speaker 4: obviously SpaceX good thing they want because they're obviously one 493 00:20:57,000 --> 00:20:59,680 Speaker 4: hundred times better than they alternative. Frankly, after doing Palenteer, 494 00:20:59,680 --> 00:21:02,160 Speaker 4: I said, this defense stuff is just really stressful. It's 495 00:21:02,200 --> 00:21:04,000 Speaker 4: really you know, hard to break into. You I'm gonna 496 00:21:04,000 --> 00:21:06,000 Speaker 4: do out of par instead. Turns out you guys are 497 00:21:06,040 --> 00:21:09,720 Speaker 4: stressful too. But but but you know, I'm like, I've 498 00:21:09,760 --> 00:21:12,399 Speaker 4: done enough defense. And we started up being pretty bullish 499 00:21:12,440 --> 00:21:14,280 Speaker 4: on things going on between China and the US, and 500 00:21:14,359 --> 00:21:16,840 Speaker 4: very naively thought the world is just gonna go in 501 00:21:16,880 --> 00:21:19,800 Speaker 4: a kind of more peaceful, more prosperous direction. And we 502 00:21:19,840 --> 00:21:23,159 Speaker 4: saw this guy is Shiji Ping come in and I 503 00:21:23,160 --> 00:21:25,080 Speaker 4: have friends with a lot of guys who built these 504 00:21:25,080 --> 00:21:26,960 Speaker 4: companies in China. A lot of them believe in free 505 00:21:27,040 --> 00:21:29,560 Speaker 4: markets read Milton Friedman, like share a lot of our values. 506 00:21:29,560 --> 00:21:31,960 Speaker 4: These are not just because they're Chinese. They're not about people, 507 00:21:32,119 --> 00:21:35,159 Speaker 4: you know, they're not CCP themselves. And we saw Suji 508 00:21:35,200 --> 00:21:37,040 Speaker 4: Pink start cracking down on these guys. A lot of 509 00:21:37,040 --> 00:21:40,160 Speaker 4: them disappeared. They have had multiple friends who knew really 510 00:21:40,200 --> 00:21:42,280 Speaker 4: well who died in their sleep in their forties, you know, 511 00:21:42,320 --> 00:21:46,040 Speaker 4: after being tech billionaires. And we saw him also making 512 00:21:46,080 --> 00:21:48,080 Speaker 4: a lot of our friends force their top engineers to 513 00:21:48,119 --> 00:21:50,520 Speaker 4: work on defense projects. Obviously we don't do that in 514 00:21:50,600 --> 00:21:53,520 Speaker 4: the US, but this became very concerning because China does 515 00:21:53,600 --> 00:21:56,240 Speaker 4: have really top talent and they are forcing them to 516 00:21:56,240 --> 00:21:58,880 Speaker 4: build new things in defense hardware. Meanwhile, in the US, 517 00:21:59,000 --> 00:22:02,280 Speaker 4: those old companies that solidated in the nineties, they're hiring 518 00:22:02,280 --> 00:22:04,840 Speaker 4: basically none of our smartest friends. So this is a crisis. 519 00:22:04,880 --> 00:22:08,359 Speaker 4: You have China building really new advanced defense things. You 520 00:22:08,400 --> 00:22:10,879 Speaker 4: have us spending lots of money very wastefully with without 521 00:22:10,880 --> 00:22:12,800 Speaker 4: top talent. And we said, wow, we need to get 522 00:22:12,800 --> 00:22:15,359 Speaker 4: back in and fix this. So Palmer with three of 523 00:22:15,359 --> 00:22:19,040 Speaker 4: my old palanteer guys, after you know, after selling Oculus 524 00:22:19,040 --> 00:22:21,320 Speaker 4: to Facebook, and they kicked him out of Facebook because 525 00:22:21,440 --> 00:22:22,800 Speaker 4: he did some politics they didn't like. 526 00:22:22,840 --> 00:22:23,440 Speaker 2: He's on the right. 527 00:22:23,880 --> 00:22:26,320 Speaker 4: But so he and these guys start this new company 528 00:22:26,359 --> 00:22:29,480 Speaker 4: nearby here and it's become the most important new defense 529 00:22:29,560 --> 00:22:32,199 Speaker 4: prime in hardware. They have all sorts of products. The 530 00:22:32,280 --> 00:22:34,800 Speaker 4: one you should check out onlines called the Roadrunner. If 531 00:22:34,800 --> 00:22:36,919 Speaker 4: you've ever seen Elon's rockets that kind of go up 532 00:22:37,119 --> 00:22:40,240 Speaker 4: and land themselves. He has the same thing for advanced missiles. 533 00:22:40,240 --> 00:22:42,400 Speaker 4: And so these missiles come in his box and it'll 534 00:22:42,440 --> 00:22:44,879 Speaker 4: go up and it'll track and destroy the bad guys. 535 00:22:44,960 --> 00:22:46,639 Speaker 4: But if not, if you don't use it, if it 536 00:22:46,640 --> 00:22:48,560 Speaker 4: doesn't explode, it'll come back in a land and it'll 537 00:22:48,560 --> 00:22:50,680 Speaker 4: wait to be used again. And so not only is 538 00:22:50,720 --> 00:22:52,800 Speaker 4: it like the twelfth the cost of a Patriot missile, 539 00:22:53,160 --> 00:22:55,720 Speaker 4: it also can be reused we're actually putting member that 540 00:22:56,200 --> 00:22:58,800 Speaker 4: ePRESS company that shoots things down with microwave radiation. We're 541 00:22:58,800 --> 00:23:00,280 Speaker 4: putting it up with that on it. So you can 542 00:23:00,440 --> 00:23:03,240 Speaker 4: imagine a swarm of these going flying, shooting that, turning 543 00:23:03,240 --> 00:23:05,359 Speaker 4: things off and coming back and landing to use it again. 544 00:23:05,720 --> 00:23:08,159 Speaker 4: And you know, modern warfare is gonna be swarms of 545 00:23:08,200 --> 00:23:11,600 Speaker 4: autonomous small vessels, small drones like all these things. And 546 00:23:12,400 --> 00:23:13,920 Speaker 4: we can't afford to do what we've been doing with 547 00:23:13,960 --> 00:23:15,760 Speaker 4: the defense primes, which is to build things that are 548 00:23:16,000 --> 00:23:19,159 Speaker 4: way too expensive, kind of last generations technology, and you're 549 00:23:19,200 --> 00:23:21,439 Speaker 4: gonna run out of them against against the swarms our 550 00:23:21,600 --> 00:23:23,479 Speaker 4: adversaries are gonna have, so we're really trying to make 551 00:23:23,480 --> 00:23:24,400 Speaker 4: sure we stay ahead of them. 552 00:23:24,560 --> 00:23:28,479 Speaker 1: So I want to combine two things you mentioned, the 553 00:23:28,520 --> 00:23:34,040 Speaker 1: new technologies swarming and the massive overcapacity to build chips 554 00:23:34,080 --> 00:23:37,560 Speaker 1: of China versus the US. What have we learned from 555 00:23:37,560 --> 00:23:41,040 Speaker 1: the Russian invasion of Ukraine and how the Ukrainians are 556 00:23:41,040 --> 00:23:45,200 Speaker 1: defending themselves with technology. How can that be applied towards 557 00:23:45,680 --> 00:23:49,240 Speaker 1: any potential invasion of Taiwan by China. 558 00:23:49,440 --> 00:23:52,800 Speaker 4: Yeah, so I mean Palans here, and uh Palnce here, 559 00:23:52,800 --> 00:23:55,640 Speaker 4: and Androl Palmer's company are very active in Ukraine doing 560 00:23:55,640 --> 00:23:57,320 Speaker 4: a lot of doing a lot of important things there. 561 00:23:58,520 --> 00:24:01,439 Speaker 4: We've learned it's about dorn droness. We learned it about costs. So, 562 00:24:01,480 --> 00:24:04,080 Speaker 4: for example, the US makes these anti radiation missiles that 563 00:24:04,119 --> 00:24:06,119 Speaker 4: are three million dollars each. We sold three hundred of 564 00:24:06,119 --> 00:24:07,920 Speaker 4: them to Poland I think a few months ago for 565 00:24:07,920 --> 00:24:11,160 Speaker 4: a billion dollars. And these missiles are able to find 566 00:24:11,240 --> 00:24:13,760 Speaker 4: jammers and take them out. Russia's figured out how to 567 00:24:13,760 --> 00:24:15,960 Speaker 4: build these gammers, and these gemmers, by the way, they 568 00:24:16,000 --> 00:24:19,040 Speaker 4: stop artillery from targeting. They really are dominant on the battlefield. 569 00:24:19,040 --> 00:24:20,800 Speaker 4: So it's electronic warfare. They figure out how to build 570 00:24:20,800 --> 00:24:23,560 Speaker 4: them like twenty thirty thousand dollars. You can't win a 571 00:24:23,600 --> 00:24:26,080 Speaker 4: war with three million dollar things being use to take 572 00:24:26,119 --> 00:24:28,439 Speaker 4: out thirty thousand dollar things. You're just gonna run out 573 00:24:28,440 --> 00:24:30,040 Speaker 4: of No matter how rich you are, you're gonna run 574 00:24:30,040 --> 00:24:31,480 Speaker 4: out of money on the battlefields. A war is like 575 00:24:31,520 --> 00:24:34,520 Speaker 4: an engineering thing where it's about scarcity, right, And so 576 00:24:34,800 --> 00:24:38,560 Speaker 4: we've learned you have to build cheaper, smarter, distributed systems, 577 00:24:39,040 --> 00:24:41,920 Speaker 4: and you know, the electronic warfare stuf's fascinating. I listen, 578 00:24:42,000 --> 00:24:44,199 Speaker 4: there's a lots of smart people who are against us 579 00:24:44,240 --> 00:24:46,600 Speaker 4: going into Russia, like we probably should be careful with 580 00:24:46,680 --> 00:24:48,320 Speaker 4: nuclear power. So I'm not gonna say this is good 581 00:24:48,400 --> 00:24:51,520 Speaker 4: or not, but it's interesting. Ukraine was able to basically 582 00:24:51,560 --> 00:24:54,760 Speaker 4: create like these electronic warfare bubbles by figuring out how 583 00:24:54,800 --> 00:24:57,200 Speaker 4: to jam sensors in different ways and kind of create 584 00:24:57,240 --> 00:25:00,680 Speaker 4: a protection bubble around their forces. Is that then did 585 00:25:00,680 --> 00:25:03,800 Speaker 4: the major incursion and it was all about electronic warfare 586 00:25:03,840 --> 00:25:06,199 Speaker 4: and turning on and off these sensors along with like 587 00:25:06,240 --> 00:25:09,200 Speaker 4: how to manipulate swarms and so battlefield is totally changing 588 00:25:09,240 --> 00:25:11,680 Speaker 4: versus how we do these things twenty years ago. And 589 00:25:11,880 --> 00:25:13,960 Speaker 4: we're trying to make sure we build companies here in 590 00:25:14,080 --> 00:25:16,800 Speaker 4: technologies general response to this and go fast on it. 591 00:25:16,600 --> 00:25:20,360 Speaker 1: So all of these ships, that giant ships that China's building, 592 00:25:21,040 --> 00:25:23,960 Speaker 1: is it likely or possible that there will be a 593 00:25:24,119 --> 00:25:28,480 Speaker 1: small autonomous swarm of vessels that counter balance that. 594 00:25:29,600 --> 00:25:32,280 Speaker 4: Well, China's pretty smart, so I think they're mostly building submarines, 595 00:25:32,320 --> 00:25:36,760 Speaker 4: which are difficult. But yes. So Saronic is the latest 596 00:25:36,760 --> 00:25:39,200 Speaker 4: company we helped starts run by a former nav cl 597 00:25:39,240 --> 00:25:42,040 Speaker 4: of eleven years in Austin, Texas. Law of the Admirals 598 00:25:42,080 --> 00:25:44,200 Speaker 4: of the Fleet are very involved, and what we're doing 599 00:25:44,680 --> 00:25:46,600 Speaker 4: is gonna is We're even next year in Austin. We're 600 00:25:46,600 --> 00:25:48,760 Speaker 4: gonna have six hundred ships we build that are twenty 601 00:25:48,760 --> 00:25:51,640 Speaker 4: four feet, fourteen feet and six feet. These are weaponized 602 00:25:51,640 --> 00:25:54,639 Speaker 4: automus vessels. We're teaching a navy how to use AI 603 00:25:54,840 --> 00:25:56,840 Speaker 4: to have the coordinate. So what we showed them when 604 00:25:56,840 --> 00:25:59,240 Speaker 4: they agree is we can basically triple the battle effectiveness 605 00:25:59,280 --> 00:26:01,639 Speaker 4: of our fleet by complementing all the big ships of 606 00:26:01,640 --> 00:26:05,040 Speaker 4: the line with about thirty smaller weaponized vessels that swarm 607 00:26:05,080 --> 00:26:06,840 Speaker 4: and coordinate and help in different ways. 608 00:26:06,680 --> 00:26:08,560 Speaker 2: It's kind of fun. It's like a little video game 609 00:26:08,640 --> 00:26:08,960 Speaker 2: sort of thing. 610 00:26:08,960 --> 00:26:10,520 Speaker 4: I actually have a lot of La Vido game talent 611 00:26:10,560 --> 00:26:13,199 Speaker 4: helping us map it out and practice battles and stuff. 612 00:26:13,359 --> 00:26:15,680 Speaker 4: But no, yes, we have to do lots of small 613 00:26:15,680 --> 00:26:17,040 Speaker 4: ships if we want to stay ahead of them. And 614 00:26:18,080 --> 00:26:20,880 Speaker 4: unfortunately our DoD is not as competent as it used 615 00:26:20,880 --> 00:26:22,520 Speaker 4: to be. But our private companies are the best in 616 00:26:22,520 --> 00:26:24,400 Speaker 4: the world. So we're going to keep getting involved same 617 00:26:24,440 --> 00:26:26,439 Speaker 4: as private companies did in World War Two and make 618 00:26:26,440 --> 00:26:27,639 Speaker 4: sure we stay ahead of the bad guys. 619 00:26:28,200 --> 00:26:29,960 Speaker 3: So let's shift gears. 620 00:26:30,000 --> 00:26:32,520 Speaker 1: I want to talk about open GOV which is another 621 00:26:32,560 --> 00:26:36,160 Speaker 1: product project of yours. You provide software for over two 622 00:26:36,240 --> 00:26:39,280 Speaker 1: thousand municipalities and state agencies. 623 00:26:39,920 --> 00:26:41,560 Speaker 3: What was that adoption practice? 624 00:26:41,640 --> 00:26:41,720 Speaker 1: Like? 625 00:26:41,760 --> 00:26:42,680 Speaker 3: How long did that take? 626 00:26:43,560 --> 00:26:46,320 Speaker 4: Well, we sold open gov earlier this year for one 627 00:26:46,320 --> 00:26:48,960 Speaker 4: point eight billion dollars to Cox. And you know, originally, 628 00:26:49,000 --> 00:26:51,520 Speaker 4: my friends and I we were wondering why California was 629 00:26:51,560 --> 00:26:53,480 Speaker 4: taxing us so much and where they were spending the money. 630 00:26:53,520 --> 00:26:56,639 Speaker 4: This is about thirteen fourteen years ago. And so I 631 00:26:56,680 --> 00:26:59,320 Speaker 4: got about twenty Stanford students in a nonprofit at first, 632 00:26:59,320 --> 00:27:01,240 Speaker 4: and we tried to just put everything online. 633 00:27:01,359 --> 00:27:02,639 Speaker 2: It was great. I didn't have my name on it. 634 00:27:02,680 --> 00:27:04,760 Speaker 4: So all these students get getting attacked by the unions 635 00:27:04,760 --> 00:27:06,320 Speaker 4: because they really don't like it when you show them 636 00:27:06,400 --> 00:27:08,800 Speaker 4: spending lots of money and government departments. So it basically 637 00:27:08,880 --> 00:27:11,359 Speaker 4: showed that California had a bunch of departments that were 638 00:27:11,359 --> 00:27:14,000 Speaker 4: dominated by the special interests, that we're spending about fifty 639 00:27:14,040 --> 00:27:16,360 Speaker 4: to sixty percent more than this was thirteen years ago 640 00:27:16,359 --> 00:27:17,520 Speaker 4: than you'd imagine by the model. 641 00:27:17,600 --> 00:27:18,720 Speaker 2: Right, of course, it's corrupt. 642 00:27:19,080 --> 00:27:21,560 Speaker 4: And all these cities started emailing us saying, oh, this 643 00:27:21,600 --> 00:27:23,280 Speaker 4: is really cool, show us for our spending. 644 00:27:23,320 --> 00:27:24,280 Speaker 2: Are we doing something good? 645 00:27:24,359 --> 00:27:27,240 Speaker 4: Or not. And we said, sure, send us the data, 646 00:27:27,320 --> 00:27:29,600 Speaker 4: and the cities would say, well, how do we send 647 00:27:30,000 --> 00:27:32,399 Speaker 4: the data over? And we looked into it and there's 648 00:27:32,440 --> 00:27:35,399 Speaker 4: tens of thousands of municipalities in the US and they 649 00:27:35,440 --> 00:27:37,600 Speaker 4: mostly don't have access to their own information. They have 650 00:27:37,640 --> 00:27:40,159 Speaker 4: to pay their IT consultants huge amounts of money to 651 00:27:40,160 --> 00:27:41,960 Speaker 4: do a report. They couldn't even see what they're spending 652 00:27:42,040 --> 00:27:45,159 Speaker 4: versus city next door for similar services. And so we 653 00:27:45,240 --> 00:27:47,159 Speaker 4: decided to build this thing called open gup and we 654 00:27:47,160 --> 00:27:48,560 Speaker 4: build a way for them to see all their data. 655 00:27:48,600 --> 00:27:51,080 Speaker 4: And then we realized governments don't like paying for new things. 656 00:27:51,080 --> 00:27:52,840 Speaker 4: They only can pay for the things they're already doing. 657 00:27:53,160 --> 00:27:54,680 Speaker 4: So we built a bunch of software for them to 658 00:27:54,760 --> 00:27:57,280 Speaker 4: run all their budgeting and their transparency and their processes 659 00:27:57,320 --> 00:27:58,240 Speaker 4: and asset management. 660 00:27:58,440 --> 00:28:00,119 Speaker 2: And it just built a big gup tech comp. 661 00:28:00,600 --> 00:28:03,359 Speaker 1: So I'm kind of fascinated how you've bounced the cross 662 00:28:03,400 --> 00:28:09,400 Speaker 1: sectors big data, defense, government, healthcare, finance, even now education. 663 00:28:10,160 --> 00:28:13,720 Speaker 1: How do you approach learning a space that you have 664 00:28:13,920 --> 00:28:14,800 Speaker 1: been in before. 665 00:28:16,160 --> 00:28:19,520 Speaker 4: Well, you know, the for building these companies and for 666 00:28:19,560 --> 00:28:22,840 Speaker 4: succeeding as an investor and ventor. There's really two things 667 00:28:22,840 --> 00:28:26,840 Speaker 4: that matter. The most one is the very top technology 668 00:28:26,880 --> 00:28:29,240 Speaker 4: talent and technology cultures. So culture is a places like 669 00:28:29,240 --> 00:28:31,560 Speaker 4: Opto where we're iterating with you. It's because we have 670 00:28:31,640 --> 00:28:34,320 Speaker 4: like these really amazing talented people who are building really 671 00:28:34,400 --> 00:28:37,080 Speaker 4: quickly and who are speaking to people and getting feedback 672 00:28:37,119 --> 00:28:39,200 Speaker 4: with them. And the other thing we're looking for is 673 00:28:39,240 --> 00:28:42,280 Speaker 4: like where is a gap in the world, where is 674 00:28:42,320 --> 00:28:44,479 Speaker 4: something Here's where it could be, and here's where it 675 00:28:44,520 --> 00:28:46,520 Speaker 4: is now. So again with so I think, go back 676 00:28:46,560 --> 00:28:49,160 Speaker 4: to all and think about that. It's very clear there's 677 00:28:49,160 --> 00:28:51,440 Speaker 4: a gap. The incentives are misaligned for how people are 678 00:28:51,480 --> 00:28:54,400 Speaker 4: accessing alts, the platforms are wasting a lot of their time, 679 00:28:54,960 --> 00:28:56,800 Speaker 4: and it's just it's not easy for them to see 680 00:28:56,800 --> 00:28:58,680 Speaker 4: what the best things are and to really quickly iterate 681 00:28:58,720 --> 00:28:59,680 Speaker 4: and do their. 682 00:28:59,640 --> 00:29:01,880 Speaker 2: Job for the clients. And so it's very obvious there's 683 00:29:01,880 --> 00:29:02,440 Speaker 2: a gap there. 684 00:29:02,680 --> 00:29:05,720 Speaker 4: And so what you do is you use UCLA hypothesis. 685 00:29:05,960 --> 00:29:08,200 Speaker 4: You get a really great tech culture where the people 686 00:29:08,240 --> 00:29:11,240 Speaker 4: at opto own a bunch of the company themselves, are 687 00:29:11,280 --> 00:29:13,560 Speaker 4: really talented people who've had wins before, know how to 688 00:29:13,600 --> 00:29:15,520 Speaker 4: build and iterate in texts that from out of par 689 00:29:15,680 --> 00:29:17,800 Speaker 4: or from other places. And then and then, and then 690 00:29:17,840 --> 00:29:19,520 Speaker 4: you build and you iterate with clients because no matter 691 00:29:19,560 --> 00:29:21,040 Speaker 4: how smart we think, we are going to come to 692 00:29:21,040 --> 00:29:22,560 Speaker 4: you and show it to you. There's gonna be things 693 00:29:22,560 --> 00:29:23,800 Speaker 4: that are wrong. There's gonna be things that are not 694 00:29:23,840 --> 00:29:26,280 Speaker 4: useful for you. But because you have a great tech culture, 695 00:29:26,480 --> 00:29:28,360 Speaker 4: you can iterate very quickly and learn. And so the 696 00:29:28,360 --> 00:29:30,600 Speaker 4: company's now been around for a few years, is now 697 00:29:30,680 --> 00:29:32,440 Speaker 4: the point where people are starting to really love it 698 00:29:32,440 --> 00:29:34,800 Speaker 4: because they've been, you know, doing a based on feedback. 699 00:29:34,840 --> 00:29:37,280 Speaker 4: So when you approach a new space, it's not about 700 00:29:37,280 --> 00:29:39,479 Speaker 4: being an expert in this space. It's about having a 701 00:29:39,520 --> 00:29:42,800 Speaker 4: really amazing culture that talks to the experts and learns 702 00:29:42,800 --> 00:29:44,360 Speaker 4: from them and builds with them over time. 703 00:29:45,040 --> 00:29:47,600 Speaker 1: And Joe, I love this quote of yours and I 704 00:29:47,680 --> 00:29:51,040 Speaker 1: have to ask you about it. My passions are repairing 705 00:29:51,160 --> 00:29:58,280 Speaker 1: broken industries and government in calculating classical virtues, prioritizing families, 706 00:29:58,520 --> 00:30:03,880 Speaker 1: and enabling a free and prosperous society. I'm kind of politician, right, 707 00:30:03,880 --> 00:30:06,440 Speaker 1: you're running, well, discuss the quote. 708 00:30:06,560 --> 00:30:08,960 Speaker 3: I can't imagine you're ever running for office, are you. 709 00:30:09,520 --> 00:30:12,040 Speaker 4: Sounds like it'd be a horrible job, to be honest, 710 00:30:12,120 --> 00:30:17,080 Speaker 4: I listen, our society is facing a lot of really 711 00:30:17,120 --> 00:30:19,160 Speaker 4: broken things right now. There's a lot of stuff that's wrong, 712 00:30:19,160 --> 00:30:21,480 Speaker 4: and I think I think virtue, classical virtues are missing 713 00:30:21,480 --> 00:30:24,520 Speaker 4: in our society. I think courage is not a virtue 714 00:30:24,520 --> 00:30:25,800 Speaker 4: that's taught to our lead. If you go to a 715 00:30:25,880 --> 00:30:29,040 Speaker 4: top one hundred university, you are taught the opposite of courage. 716 00:30:29,080 --> 00:30:32,320 Speaker 4: You're taught to shut up, virtue signal, go along, don't 717 00:30:32,320 --> 00:30:35,120 Speaker 4: think for yourself, don't oppose the borg. Whatever they say 718 00:30:35,160 --> 00:30:38,240 Speaker 4: is right, and it's really broken. I think it's really 719 00:30:38,320 --> 00:30:40,280 Speaker 4: scary what we face in our society right now. So 720 00:30:40,720 --> 00:30:42,840 Speaker 4: you know, I think the fundamental units of the West 721 00:30:42,880 --> 00:30:46,840 Speaker 4: are the classical virtues, are the liberty values around the Enlightenment, 722 00:30:47,160 --> 00:30:50,560 Speaker 4: are our functional families with two parent households. I think 723 00:30:50,600 --> 00:30:52,840 Speaker 4: these are all things that make our society functional. And 724 00:30:52,880 --> 00:30:54,680 Speaker 4: if we don't say it and we don't fight for it, 725 00:30:54,720 --> 00:30:56,240 Speaker 4: we're gonna have a really broken society. 726 00:30:56,560 --> 00:30:57,120 Speaker 3: All right. 727 00:30:57,160 --> 00:30:59,400 Speaker 1: We have time for a couple of questions from Slido. 728 00:30:59,520 --> 00:31:02,880 Speaker 1: Let's take look, what do you look for when evaluating 729 00:31:02,960 --> 00:31:05,680 Speaker 1: fund managers for yourself and your family office? 730 00:31:07,240 --> 00:31:11,200 Speaker 4: So when I'm looking for fund managers, I mean for me, 731 00:31:11,320 --> 00:31:13,680 Speaker 4: because I have a network with these people. I want 732 00:31:13,720 --> 00:31:17,680 Speaker 4: to know that a lot of my friends really respect them. 733 00:31:17,680 --> 00:31:19,840 Speaker 2: I want to know they have some unfair advantages. 734 00:31:20,280 --> 00:31:22,719 Speaker 4: I want to know that they have obviously an amazing 735 00:31:22,760 --> 00:31:24,920 Speaker 4: track record, and then I want to know that there's 736 00:31:24,960 --> 00:31:26,920 Speaker 4: some reason why they're still in the game and focus. 737 00:31:27,000 --> 00:31:28,360 Speaker 4: I think a lot of people who've had a lot 738 00:31:28,400 --> 00:31:31,280 Speaker 4: of success, there's various things happen in their lives and 739 00:31:31,280 --> 00:31:32,200 Speaker 4: they're no longer working. 740 00:31:32,200 --> 00:31:33,320 Speaker 2: They all long have the same. 741 00:31:33,120 --> 00:31:34,760 Speaker 4: Culture, So I mean, I want to know the culture 742 00:31:34,760 --> 00:31:37,080 Speaker 4: of the organization around them at their fund and know 743 00:31:37,120 --> 00:31:39,120 Speaker 4: that they are still working as hard as they were 744 00:31:39,440 --> 00:31:41,560 Speaker 4: when they first created that, you know, for the first success, 745 00:31:41,560 --> 00:31:43,640 Speaker 4: because I think that's that's something that slips very easily, 746 00:31:43,640 --> 00:31:44,680 Speaker 4: so you got to watch out for it. 747 00:31:44,880 --> 00:31:48,680 Speaker 1: And here's a perfect question to wrap up on what 748 00:31:48,720 --> 00:31:52,680 Speaker 1: are the most exciting trends you're seeing in the marketplace today? 749 00:31:52,760 --> 00:31:54,760 Speaker 4: So the most exciting trend by far, I started to 750 00:31:54,800 --> 00:31:58,000 Speaker 4: hint at it earlier is what's going on with applying 751 00:31:58,080 --> 00:32:01,200 Speaker 4: AI to services industries. There's about five trillion dollars of 752 00:32:01,240 --> 00:32:04,360 Speaker 4: wages in the US in the services sector. Over two 753 00:32:04,360 --> 00:32:07,200 Speaker 4: trillion dollars of those wages are in the areas where 754 00:32:07,240 --> 00:32:10,040 Speaker 4: we've already shown you can double the proctivity, in some 755 00:32:10,080 --> 00:32:13,120 Speaker 4: cases triple the cash flow from these old legacy businesses. 756 00:32:13,480 --> 00:32:16,120 Speaker 4: This is a whole new area of tech enabled services 757 00:32:16,120 --> 00:32:17,000 Speaker 4: that actually works. 758 00:32:17,040 --> 00:32:17,280 Speaker 2: Now. 759 00:32:17,600 --> 00:32:21,520 Speaker 4: We're seeing, example, healthcare billing two to eighty billion dollar revenue, 760 00:32:21,560 --> 00:32:25,320 Speaker 4: industry typical margins twenty percent. We already have companies getting 761 00:32:25,320 --> 00:32:28,480 Speaker 4: fifty sixty percent margin. Fixing that space, there's huge parts 762 00:32:28,520 --> 00:32:31,440 Speaker 4: of our economy. We're gonna have proctivity shoot upwards. If 763 00:32:31,440 --> 00:32:33,320 Speaker 4: we can manage not to break our country with the 764 00:32:33,360 --> 00:32:35,440 Speaker 4: stupid government stuff the next several years, we're gonna have 765 00:32:35,520 --> 00:32:36,640 Speaker 4: a very productive society. 766 00:32:36,800 --> 00:32:40,000 Speaker 1: That was my conversation with Joe Lonsdale. He is the 767 00:32:40,040 --> 00:32:42,920 Speaker 1: co founder of Palanteer, as well as a number of 768 00:32:42,960 --> 00:32:47,520 Speaker 1: other finance and technology related startups. I thought the discussion 769 00:32:47,560 --> 00:32:49,800 Speaker 1: was fascinating and I can't wait to get him in 770 00:32:49,840 --> 00:32:52,800 Speaker 1: the studio for a full ninety minutes to really do 771 00:32:52,880 --> 00:32:57,320 Speaker 1: a deep dive into his career. If you enjoy this conversation, 772 00:32:57,520 --> 00:32:59,160 Speaker 1: well be showing and check out any of the five 773 00:32:59,280 --> 00:33:04,080 Speaker 1: hundred previous discussions we've had over the past ten years. 774 00:33:04,440 --> 00:33:08,960 Speaker 1: You can find those at iTunes, Spotify, Bloomberg YouTube, wherever 775 00:33:09,040 --> 00:33:12,080 Speaker 1: you find your favorite podcasts, and be sure and check 776 00:33:12,080 --> 00:33:15,800 Speaker 1: out my new short form podcast, At the Money ten 777 00:33:15,840 --> 00:33:20,560 Speaker 1: minute discussions with experts about topics related to your money, 778 00:33:20,920 --> 00:33:25,240 Speaker 1: earning it, spending it, and most importantly, investing it. At 779 00:33:25,240 --> 00:33:28,200 Speaker 1: the Money in the Master's in Business, feed or wherever 780 00:33:28,240 --> 00:33:42,560 Speaker 1: you get your favorite podcasts,