Invest Like the Best with Patrick O'Shaughnessy - Christian Rudder – The Quantified Self - [Invest Like the Best, EP.05]

Episode Date: October 11, 2016

In this episode Patrick talks to Christian Rudder, who is the co-founder of dating service OK Cupid, a NY Times best-selling author, data and math junky, and musician. Patrick and Christian discuss interesting trends in OK Cupids dating data, artificial intelligence, the NSA, great books on the Civil War, and more.  Please enjoy!   For comprehensive show notes on this episode go to investorfieldguide.com/rudder/ For more episodes go to InvestorFieldGuide.com/podcast.  Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub Follow Patrick on twitter at @patrick_oshag

Hello and welcome, everyone. I'm Patrick O'Shaughnessy, and this is Invest like the Best. This show is an open-ended exploration of markets, ideas, methods, stories, and of strategies that will help you better invest both your time and your money. You can learn more and stay up to date at investorfield guide.com. Patrick O'Shaunisee is a principal and portfolio manager at O'Shaunicee Asset Management. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of O'Shaunice Asset Management. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Ashonasi asset management may maintain positions in the securities discussed in this podcast.

My guest today is Christian Rudder, who is the first of hopefully many guests who are not investors per se. Christian's career arc seems too interesting to be true. He's best known as a founder and CEO of OKCupid, the popular dating site, but I'll let him walk you through the rest. He's a data and math junkie, a musician, and a very interesting thinker and business person. We discuss, among other things, interesting trends in OkCupid's data, artificial intelligence, the NSA, and great books on the Civil War. For show notes, visit investorfieldguide.com forward slash rudder, RUDDR. And now, please enjoy my conversation with Christian Rudder.

Good morning, Christian. Thanks very much for doing this with me today. maybe we'll start with a couple origin stories, one very short, how I came to be in your living room this morning, and then a little bit longer one, kind of your backstory, since a lot of people won't be familiar. Certainly will be familiar with your work and your businesses, but maybe not you personally. So just so people know, since it's kind of an odd connection, I met Christian through Jeff Graham, who was the first episode guest on the podcast, friends, I think, for a long time, and he

recommended that I reach out to Christian, and it turned out in the course of our conversation, that I was a huge fan of Dataclism, Christian's book. So tiny little world here and really excited to be here with you today. Well, thanks for having me. I'm glad to be here. So maybe we could start with your story, kind of a quick narrative, kind of the highlights of your career, mainly because it's kind of been all over the place. You've done a lot of interesting things.

And I'm particularly most interested in the transitions and how sometimes a career flows very naturally. It seems like you've jumped from entire different. arenas to new arenas. So maybe how you got to each spot. Yeah, I mean, it'll be hard to kind of connect it into a whole theory or a whole story. I mean, I guess I was a founder of OKCupid, which is a dating site. That's probably the kind of temp poll of my life, I guess. I was also the main songwriter in a band called Bishop Allen also played in the band. I was one of the people who helped make Spark Notes. I wasn't a founder, but joined very early on, which is Spark Notes are like study guides. kind of modern day Cliffs notes, I guess.

And I wrote Dataklism, as you know. And I guess I did that not chronologically. I guess what was the first major? Was it the band? Like when you came out of school, what did you do write out of school? Well, when I came out of school, I was actually working. I had started this, I won't even call it a software company, but I wrote this program with my friend called Report Engine, which was like for stockbrokers.

It was like a random idea. My girlfriend's dad at the time was a stockbroker. and he needed something and I made it. What did it do? Did it pull? It didn't even pull away. Like we weren't even like that ahead of the game. This was like 98.

So yeah, you entered in from statements what was going on in an account and it made all these really nice reports and charts and stuff actually a lot like how dataclysm ended up to kind of tie the room together, so to speak. So we did that. We really didn't know what we were doing. We sold a few copies of it, but unquestionably a failure.

It didn't really go anywhere. And then I moved to Austin. where I was there for like three months, and my main job was baking bread at this place, Texas French bread. But while I was there, this was like spring of 99. So this was like the heyday of like internet boomtown. I applied for a bunch of random.com jobs. And one of them was for the spark.com, aka spark notes. I got that job. I sent in some writing samples. They hired me. It turns out they were also Harvard guys. And I knew them, one of them for math class. I was a math major. But I was hired to be a comedy writer essentially.

and make basically viral content. The Spark was one of the few places that was making viral stuff back then. We had like the first online purity test. I mean, this is like, you know, this is like Paleolithic Internet Times, basically, you know. So how did it work? Because I remember using SparkNotes in college. But basically just going to the books page and using that content. This is like way before.

I mean, you're 31, right? So this is way before you ever would have used it. It used to be the Spark and Spark notes is two separate URLs. The Spark was like the stuff that brought people to SparkNotes. It was kind of a genius plan, which I didn't think of, so I can say that. It was like the Spark had tons of time wasting stuff, like things to read, dumb tests to take, all of this kind of thing, toys, web toys, and that would appeal to high school and college students. And so they would pass all these things around, waste their time, not study while they're playing around on the Spark. Lo and behold, hey, a student who hasn't studied, check out our new product, Spark Notes, which when I joined, I think only had Hamlet and maybe Macbeth.

So only had two guides. We offered Spark Notes to kind of like solve the problem that we had, that we had created. And Spark notes took off. And later they shut down the Spark after I left because it was kind of one of these things, me and my friend and OKCupid co-founder, Chris Coyne. We wrote everything. And as soon as we were gone, there was kind of no point to continue. Spark Notes was big enough on its own at that point.

Anyway, so I left Spark Notes in 2002. We started OkCupid in 2003, really right around the same time that I started the band, Bishop Allen, kind of did both of those things at once. The first few years were more Bishop Allen than OKCupid. And then once I started writing the blog for OKCupid where we kind of took all our data and, you know, analyzed it, had had some kind of cool graphs about race and sex and attraction and all that stuff. That was about 2009. Then I just kind of was full-time OKCupid until I left OKCupid in 2015. So in the band, were you touring a lot? Were you on the road? Yeah, those years from like 2004 to say 2008 or nine was, was, was,

maybe three months out of the year I was on tour. Yeah, it was my, you know, we weren't paying ourselves for OkCupid at that point. So it was like my full-time, my only real job at that point. So it sounds like the strategy at OKCupid mimicked or took some of what worked at spark slash spark notes. Totally. And my role was. People in through really interesting content.

Exactly. My role actually at OKCupid was at least those first from, say, my first half of my OKCupid time was very similar where I was just writing stuff that would be. make people realize that okay, qubit existed in the same way I was writing stuff at Spark Notes that made people realize SparkTones existed. So I would work on the product and do a little bit of programming here and there,

but nothing serious. It's a good transition into the book, which is at least at first, I think an extension of what you were doing on the blog. Yeah, totally. But then morphs into a lot more, including, I think, some of the best chapters in the book are the later ones

where you kind of riff on things like the NSA and data in general and sort of, sort of the quantified self and the collection of data on people. Sure. And sort of identity, which is great. It's a book for everyone listening that I'm shocked. I read a lot of books. This is a book that should be Gladwellian type sales.

It is that entertaining and interesting. And the reason is because so many books today, these kind of pop-sci-type books, are regurgitations or replications of 10 academic studies with little quaint examples, little stories to illustrate those studies. And it just feels kind of all the same. It's almost always with someone else's data. And what's unique about this book is that it's your data, right? It's no one else really has access to this or had access to this. So it's trends within a data set that's very unique. Yeah, I really tried to get away from that model of, you know,

here's an academic finding and here's this kind of quirky example of it in practice that we found in that one factory in, you know, Idaho. So, but, because I knew that I had my own data to mine and I understood it probably better than anybody in the world. So it was, you know, especially writing about online data in general, but specifically data from a dating site. It's just so inherently interesting. I feel like it, I had to take advantage of that myself. So this is probably our closest area of direct overlap where both of us spend a lot of our times dealing with data. Obviously very different data sets, financial statements versus dating, dating information. But can you talk a little bit about your background?

in working with data, how, you know, what tools you use, how you learned, things like that, that people might be able to use themselves that they're interested in this field? Sure. I mean, well, like I said earlier, I was a math major. I didn't actually take a statistics class. I was mostly into, like, algebra and kind of more abstract stuff. But I, you know, a lot of the statistics and data analysis is not like rocket science. In fact, the more rocket sciencey it gets, the kind of, like,

like that usually implies the worst your data actually is. So at OkCupid, we never had to bring those tools to bear. But I use SQL. Okay, Qupid uses SQL to store the data. I would use a little bit of Python. Or I would have, for some more sophisticated things, I would have programmers write a little script for me. Or I would just take a raw dump and put it into Excel.

You know, Excel can hold, well, it can hold about a million rows, but, you know, 500,000 with some room to breathe. So I did a lot of that in Excel, just because, I've been using Excel. That very first software program report engine was originally built as this really arcane set of Excel macros. So I love that program. So I did a lot of it in Excel. Everything else is pretty much homespun.

I mean, I just kind of crunched everything just using basically the raw materials. I don't ever use things like chart beat or mixed panel or any of that stuff. I don't know. So one of the notable things about the book is the charts. and at the end, you know, you credit Tufti, which is sort of the gold standard of visualization of information. How did you build those? It doesn't look like they were built in Excel.

It looks... Oh, they're all in Excel. They are in Excel. Yeah, they're all in Excel. Was there some sort of like Tufti package or something that I don't know about or did you just No, I just did it. Yeah. You just made it work.

You just get in there. Yeah. Yeah. I mean, some of those things I used using the actual grid rather than a chart. You know, I would use the grid and they're kind of like heat mapping ability for the different cells. Yeah, I spent a lot of time in general. with that stuff. And all the graphs on the blog were done in Excel, sometimes with like JavaScript

overlays that I would write so they would animate and stuff. You know, this is like 2009, 10. There were basically no charting tools, kind of off the shelf charting tools or out of the box charting tools. So I just made everything up. So yeah. And we're doing the blog and certainly the book and this I can credit Tufti for like I really wanted to get away from like the infographic feel where everything is like super designed and there's just tons of like illustrations and everything looks very nice and that kind of generic way. I just wanted it to see. I just wanted it to seem as informational as possible or keep it as information forward as possible. This might be a peculiar question.

Maybe one of you never been asked, but why did you choose the color red in contrast? Oh, in the book? Well, I had one color to work with. Just that's what they told me. And given that, you know, like it's almost chooses itself. Like blue is too close to black. Green. It's just kind of weird.

And again, it's still dark among the kind of warmer colors. Yellow is too light. Orange. Like, I mean, the red is a little bit orangey, but, you know, It's surprisingly easy to settle on red. And it just kind of like, I mean, also, Tufti is an inspiration here. He uses the one color for endpoints on his spark lines and stuff like this in some of his books. So I was like, I'll just use this red, basically.

It worked great. The book looks great. So let's dive into some of the data in the book and some of the trends. Sure, sure. Maybe a fun one to start with. Maybe it's the low-hanging fruit, but it's a good one I think that people appreciate is this idea of Wooderson's law. Can you describe what that is? Oh, man, Wuderson's law.

Yeah, okay. Well, that Wooderson, the Wooderson in question here is Wooderson from Dazed and Confused, which is actually the reason I moved to Austin for those few months anyway, because of that movie. He says at some point in Dates and Confused, that's what I love about high school girls, man. I keep getting older, but they stay the same age. And that viewpoint is basically, at least in the data, the viewpoint of collected maleness in general. Like guys, no matter the age, always pursue the kind of the youngest woman in the group of women that they're presented with.

And so, you know, if 20-year-old guys think 20-year-old women are the hottest, that makes sense. 25-year-old guys think 20-year-old women are the hottest. Okay. 30, 40, 45-year-old guys think 20-year-old women are the hottest. And, you know, like, it's not exactly an earth-shattering conclusion. You can open a magazine and see all the models are very young. Movie stars, certainly female movie stars. There's a huge youth skew there, you know.

But it is interesting to see it play out in the real world in terms of the decisions like actual online daters are making. In their ratings of people, in how they contact guys basically go after the youngest women period. And it's different for women, right? The same sort of scatterplot is quite different. Yeah, the women one is way more sane and in fact reflects what women tell us they're after, which coincidentally is the same thing men tell us that they're after. they want someone near their same age. So women, 25-year-old woman will say she's looking for a 25-year-old guy or will,

well, she'll say she's looking for a 25-year-old guy. And then lo and behold, that's the age of guys she thinks is most attractive. 30-year-old woman thinks 30-year-old guys are most attractive. And that's also who she told us she would think was most attractive and so on, kind of up that diagonal, you know, 45-year-old women, maybe a little bit younger, but still right around their same age. Whereas, again, guys, a 35-year-old guy will tell us, oh, yeah, you know, I would love a woman who's 30, 32, 33, 34. That's what he says on the site goes through. It's all, you know, 20-year-olds.

So this is something that you kind of have to wrestle with. One of the many sort of challenges of running a dating site, there's all these kind of warts on the, especially the male, but in general, the human psyche that you have to grapple with and kind of try your best to rectify or smooth out so that the site will function. Because obviously these 20-year-old women don't want to hear from any 45-year-old guys. Right. Right. So, so, and we've got to make everybody happy running OKCupid.

So, you know, that, that's just one of the, one of the many kind of sociologically interesting and sort of professionally frustrating aspects of human behavior. One of the other things I found most interesting in the book, which I felt was very broadly applicable, pretty much no matter what you do. If you're, if you're in the business of offering a product or service, this seems to be applicable. In this case, the product or service being, you know, yourself. But the idea.

of hopefully not a service. Right. The idea of higher variance and this kind of idea of the pratfall effect that you talk about. Maybe touch on the role of variance in the success of people dating. Sure, sure. I mean, generally speaking, the better looking you are, the better you do. On a dating site, for sure, I assume, with a high degree of confidence that's also true in real life. Right. The better you do romantically.

But within a group of people who all are the same amount of good looking. so kind of a kind of like iso attractiveness band, the people who exhibit the highest variance in their appeal do by far better. And by variance, I mean you have, say you're a five out of ten, it is better to be to have half the people think you're a nine and half the people think you're a one than it is to have everyone think you're a five. That's obviously the most extreme amount of variance. I have half the people think you're extremely good looking and half the people think you're repulsive because what we found is that it's it's almost like an activation energy required in terms of someone approaching you or wanting to actually meet you in person presumably and date you

or whatever so the more variants you have in your look the better you do and so an example of a thing that people and our users have kind of realized this and I think this is something that people intuitively know in general you know you can do you have a tattoo tattoos is a kind of very easy example there's lots of people who think tattoos are super hot there are lots of people who think tattoos are just like not for them. They don't want they don't they don't want to date somebody with a ton of tattoos that works super well. Nose rings, piercings, that kind of thing. Crazy looking hair, blue hair, you know, whatever, a buzz cut on a woman, for example, or really long hair on a guy, maybe. You know, it's almost like you, you want the people who are predisposed to like you to

really like you and everybody else you don't even care. They might as well hate you essentially to use kind of extreme terms in terms of your dating outcomes. And so we found that that say a five out of 10 that has a high degree of variance gets the same amount of attention as say a conventionally attractive seven or an eight. You kind of move up a few leagues, so to speak, just by being strange-looking. So that makes sense on the top end for sure. Obviously, you know, you're getting more people rating you highly. I'm sure there's a high correlation between a high ranking and wanting to meet the person, right? And so high variance makes sense there. But like in things like book sales, for example, they've shown that actually many of the best selling books have a lot of one-star reviews

and a lot of five-star reviews. Sure. So maybe there's an element of controversy or something new and different. So tying it back to the idea of products and services, if you're just offering like an iterative, generic version of what everyone else is doing, probably not going to incite a lot of interest. If you're doing something much more new and different, some people will hate it, some people will like it.

But maybe talk about the negative side. So it makes sense. More people rank high going to reach out. But is there also an effect from, like a boosting effect from the negative ratings? We did find that. I mean, it's definitely lower than just the power of having a lot of people really like you.

But we did find that just everything else being equal, having more people dislike you strongly, slightly helps the amount of attention you get. I have no idea why my operating theory would be that, like, you know, everybody has a sense of what everybody else is, what the general perception of a person is going to be, you know. I can see somebody, and I might not find her really attractive,

but I have a good sense that like, oh, I bet a bunch of guys think she's, is hot or whatever, you know. And I think what happens is if you see somebody that you're into and you think that there are a lot of people that are not for a certain type of person, it's like, well, it's a turn on. It's kind of like a white knight effect, I guess, where you're like, a lot of people aren't going to be into this girl. My message is going to be the one, I'm going to find that diamond in the rough. I'm going to come in there and say, I really think you're beautiful. You probably don't hear, you know, implied you don't hear this that often. I think

that's what's going on. That's not the best explanation of it. It's hard to talk about this stuff without speaking in kind of broad and generally like macho terms. Just for your listeners, like I talk like this because online dating is driven by guys approaching women. You know, 90% of the activity on the site is driven by men, first contacts, ratings, all that stuff. That's true. Men are the initiators offline as well, but I think especially online, where for whatever reason, women just approach online dating a lot more passively than guys do. And so, you know, when I'm talking about guys hitting on girls and all this stuff, you know, the straight male drives like 80 to 90% of the traffic on a dating site.

You mentioned earlier the every guy, every age likes the same. You know, the formula for good-looking girls is the number 22, right? Yeah, yeah, yeah. And much different for women. Yeah. there's this issue where surveys, people will be asked what they want. And very often that doesn't actually correlate with what they do or what they act on. Do you find those gaps kind of everywhere?

I wouldn't say everywhere, but certainly, well, with that example for sure, as I was saying, like, you know, you ask guys what they want and they say they're looking for women roughly their same age, maybe a few years on either side. And then they go out and do what you just described. for race, you know, people almost universally say race is not a factor in who they think is attractive or, you know, interracial dating is great, you know, if you ask people, but they go out and act. It's like a not in my backyard type of attitude within a racial dating, for example, where people will profess to say that it's fine, but they themselves do not want to do it generally. So, yeah, you do see that quite a bit. I mean, it's not, people don't know themselves, I think.

There's also, you know, social desirability bias where they don't want to look bad to even a computer questionnaire. You know, so again, these are all, this kind of gap in what people say they want and then what they go out and do, trying to close that gap or negotiate that gap is a big part of running a dating site. For me, one of the most surprising and actually kind of upsetting, big bummer of a chapter in the book about trends in race in dating. maybe touch on what you found, kind of the high level punchline, and maybe we could get into that a little bit. Sure, yeah. I mean, I like that chapter because it speaks to the ability of data to, like, make people talk about something that they might not otherwise talk about. And what's in the chapter is it basically shows that in online dating pervasively, whether it's OKCupid match, any dating site whose data I've ever looked at, there's a very clear racial bias against black people and Asian men. from, you know, when I say against black people, I'd say from Asians and from Latinos and from whites. It's not just whites versus everyone versus, you know, what are minorities.

And essentially those three groups, black men, Asian men and black women, they have essentially 75% the experience of everyone else. You know, they get 75% the like, 75% the messages, 75% the replies. They just have a kind of lesser experience. And facing this data, working at OkieCupid, I get asked and we even ask ourselves, like, what can we do about this? It doesn't feel good to see this kind of thing happening. And this trend has been present since I first started looking at the data. Every site I've ever seen, it's just a universal, deep and broad trend.

What can we do about this? And, you know, after a lot of thought, the answer for us was like nothing. We can't make a change for the site that's going to make people less racist any more than, like, OK, Cupid could ever change society. You know, if there's a Latino man who doesn't want to talk to black women, we can't just show him. more black women, he's just going to say, well, okay, he would not show me what I want, I'm gone, you know, I'm not going to change his behavior. And he probably doesn't even realize he's voting or acting the way he is anyway. That was my belief. The only thing we figured out we could do, which would be to publicize this data and say, hey, you know, there's often a discussion of,

like, are we a post-racial society, you know, is racism really a thing anymore? You know, certainly a few years ago before all of the shootings were more made as public as they've been. This was a common perception where it's just like, you know, that, that's, so 1960 to think about racial bias, you know. And we published the stuff and said, no, here, this is really what's going on. And that actually was our most popular blog post. It's kind of the, I think, the best part of the book to show that there really are, there are types of people in America that have just a worse experience.

You know, obviously I'm looking at specifically online dating or dating in general, because I don't think it's just an online thing. And what's striking about it is that it's not, It's not, as you say, just one race with one other race. It's that when you look at other minorities, which are well represented in the sample, you don't see the same, you don't see the same thing happened. Yeah, no, no. I mean, Latinos have, for all intents and purposes, in the data the same as white people.

They have the same biases against the same groups, and they suffer no biases themselves. Yeah. You know, that's obviously different than the way it works in society at large here. or Asian women, they are part of the majority in this sense. There's a, yeah. The chapter, I think it was one chapter, one section for me was the most, and you say it's one of your favorites, which I agree with, even though it's kind of a negative, it seems to be the best example I've ever come across that sort of puts data behind this open question

of post-racial America, you know, how bad is it really? And this is sort of a definitive, it's literally in red in the book, a red stamp saying, you know, it is this bad and it's it's everywhere well the thing that i enjoyed the most about writing that chapter i agree with you it's it's depressing but the thing that i guess i like the most about that chapter is that there's very little data about person to person interactions and and how race affects those so tons of data on how this race or that race does on the sate or graduates from high school or you know income or where people live and the loans that they're getting are not getting there's very like this this class of person does better than this class of person on some third part

party thing, like a test or a loan application or whatever. There's very, very little, in fact, almost no data on like how this one group of people interacts directly with this other group of people. And online dating, because we collect race and it's very reliable information, and the people have to talk to each other, unlike on Facebook or Twitter where you kind of can just talk to your friends who are probably like you. And the people are all strangers, so there's no kind of pre-existing network laid over this whole thing.

You get to look at person to person, how do white men? interact with Asian women or how do white women interact with Asian men or or black men interact with Asian women or whatever, you know, and how did those Asian women react in turn, you know, and then you get to ask and then answer a lot of really interesting questions in a way that you can't really, it's a lens that, that you don't see very often, a way of looking at race that you don't see very often. Well, it's a great chapter, an amazing book that I highly recommend everybody check out. It is, it's not overly long. It's probably 250 pages, something like that. And it is, to my mind, one of the, one of the books that I'm surprised that not everyone has read,

primarily because, again, it's dealing with data that's not just, you know, here's an academic study and here's a silly little, you know, five-paragraph example of this study in the real world. It's a real, I don't want to say proprietary, but custom set of data from which we can learn a lot about one of the main aspects of our life, which is kind of how we interact with other people, specifically in dating, but even in broader trends than that. So maybe we could talk a little bit about books now and some of your favorites as a reader. Obviously, you've written a book and have aspirations maybe for more books. But what are some of your all-time favorites, maybe even extra points for under the radar ones that people would not have heard of?

Sure. My all-time favorite book is pretty easy. That would be Shelby Foote's three-volume history. of the Civil War. I've read it three times. When you're in a band, you have a lot of time just driving around. So I got really into like very long nonfiction. I read the three-part biography of, of, of Deodor Roosevelt, the three-part biography of Winston Churchill, tons of stuff like that. But I just love Shelby Foot Civil War. It's easily my favorite book. Let's see. I mean, I love Dune. I don't read that much science fiction or fantasy, but it's, you know, this is the way that Frank Herbert gets the kind of like interiorness and like makes this world that's like new but also plausible. I don't know. That book's also amazing. More recent stuff. I really like Look Who's Back. Have you read this book? No. It's a German book about Hitler not dying in World War II. He wakes up. It's like whatever, 2010 or something like this in Berlin. And he's just kind of like nobody really believes that he's really out of Hitler. He is. It's kind of like a farce. It's kind of amazing.

It's also frighteningly appropriate in the age of, he's very Trumpian, let me put it that way in the book. Of course, unintentionally, this is before this election cycle. That book is great. I really liked Age of Miracles. We read that. It's about, it's like a sci-fi book. I read it a couple times. It's written from the perspective of maybe she's 13 or 14-year-old girl.

The world's rotation is slowing down. And it just has this amazing tenderness. the science in it is actually kind of cool, too, but it's just a great story. Have you read Station 11? Yes. It's similar in tone. It's also an apocalyptic book written by a Brooklyn woman, but subjects are very different, but it has that kind of like feeling to it. I love that book. I love Asia Miracles. I love Station 11 too. It's a great book. I mentioned, I think I mentioned Hs for Hawk earlier. I really liked that book as well. Sounds like a lot of, a lot of nonfiction biography. Yeah, I love nonfiction. Yeah, but nonfiction and biograph.

I've definitely spent the most time with. I've read probably way too many biographies of Napoleon. I don't know. I kind of would go deep dives. Like I was like Civil War for a while. Then I was like Napoleon. I know it's also kind of a martial topic, which isn't really my thing,

but just got into it as a thing. And there's lots of stuff written about these people. Civil War I like so much because it touches on issues that are still just so relevant today with the way reconstruction went down and, you know, states' rights and Americans fighting each other. and yeah, it's just race, obviously. It's just an amazing time in American history. How do you find new books?

You know, I usually just go to the bookstore, which my bookstore is Word in Greenpoint, and I just like randomly browse and grab stuff. Like I had never read anything about Abraham Lincoln or the Civil War or anything. And one day I walked in, actually a different bookstore, but I just grabbed a couple things off the shelf and read them and loved it and got really into it.

Or same with Age of Miracles, just pull it off the shelf. maybe had a little card because it's a Brooklyn or it's a Brooklyn book. I grabbed it and seemed good. I'm kind of willing to give anything a try. I finished most things I read, though, obviously not everything. I think the book I'm reading right now is, I say this, I think, because I left it on my parents' house, so it's unclear if I'm still reading it. But SPQR about the history of ancient Rome.

I've seen that on bookstands, yeah. Yeah, it's good. It's good. It's something I didn't really know anything about. You know, I like books about stuff. I don't know what they are, that I'm not. I like when I'm unfamiliar with the topic. We talked a little bit offline about what may be your next project,

so we'd love to come at that a little bit indirectly by first asking for you to describe what math 25 and math 55 are. Oh, okay. Yeah, I mean, math 2555 is essentially a pair of math classes. 25 is the one that you can elect to take as an incoming freshman math major at Harvard. it's extremely hard. I didn't take it. And maybe 40, 45 people do. If you do well enough in the first few weeks or you have such radiant talent that they

identify it in you that quickly, you get invited to take 55, which is then you're basically invited by the Harvard Math Department to take the special class, which is for people who will eventually become professional mathematicians, essentially the best, you know, the 10 people that they pick for math 55 are probably 10 of the, best 100 their age in the world in math. This is like the Navy SEALs of math. Exactly right. And you have, you know, certainly for any other math major, the people who took 55 as

freshmen, you have this like aura about your entire career. I mentioned in the book because, you know, the NSA recruits heavily from Math 55 for its employees, from that class of people who took 55. And government workers have this reputation of being, you know, kind of lazy or whatever you think of the post office. You think sloth. You think indifference. And I mentioned this in the book because, you know, the NSA is not like that. They're the best of the best.

They're on top of it, to say the least. And so, you know, it's, you can't really talk about data without talking about government surveillance, the NSA, privacy. And I make the point. and it still holds that what the NSA is doing is powerful, and you can pretty much, even if you don't know exactly what it is, you can be guaranteed that it's being done very well. So it gets to your points earlier about collecting data on people and how we are increasingly quantified through all the major services that we use all the time

that get us coming back through these sort of like dopamine snacks that, you know, a Twitter retweet provides or something like that that gets us engaged to use the industry term. I guess the next step will be even smarter methods of getting us engaged, including artificial intelligence. Could you kind of riff on AI a bit, concerns, interests in that field? Sure, sure. Well, I guess let me start with just kind of finishing that thought about the NSA. Like with, you know, when I say what they're doing, they're doing well, I mean, they're doing it efficiently and with focus. Not necessarily what they're doing is good.

Because I think, you know, the idea of corporate data gathering and government, data gathering, just usually those two very separate things get subsumed to this one idea of all these guys have all this data about us and it's violating our privacy. And I actually think, kind of from the inside, I see it as two very different issues. The corporate side has its own problems. I mean, they're gathering data to sell you things, which is annoying. I don't like seeing ads anymore than anyone else. I don't like spam based on the emails that I've sent. However, the way they're doing it is aggregated. Advertising sells a product to a consumer, which could be all people for Coca-Cola,

but could also be for X body spray, you know, 18 to 25-year-old guys or even a more narrow slice of the world. But it's never to a particular person. Like no company, OKCupid, Facebook, Twitter. No company is pulling out individual profiles, individual people and asking, you know, what does this person want up to?

What are they into? What are they like? What are they going to do next? Who are they talking to? That never happens. It's one thing not worth the time. There's all kinds of rules in place to keep that from happening.

It's just not a thing. that's the corporate side of what corporations do with your data the government has sort of the reverse relationship nobody at the NSA is looking at what's going on and saying you know uh you know let's go let's go arrest 25 year old guys it just doesn't happen they're looking at a specific 25 year old guy who he's talking to what he's doing what he likes what he might do next with with a name and an address and a family um and uh it's far more uh pernicious and i think an invasive for that specificity. And I think it's important when people are thinking about privacy to separate the actual use

case for the data and therefore the implications for any individual. Anyhow, I think as people employ algorithms to make decisions about data or anything else, computers are obviously getting smarter. And I think I'm in that camp that thinks eventually in 20 years there will be a kind of general computer intelligence that will be as smart as a human being and therefore will quickly become way smarter than a human being and that that could have you know grave implications for the way the world works the way life exists on the planet i think you're essentially be creating a god a real god and that just is a frightening idea is there anything we can do i'm thinking about like

Asimov's rules of robotics or something. Are there things that we can do before that happens that make that God benevolent or remain under our control? What are some of the potential solutions here? Or is this just, are we just on a path that we can't get off of? Yeah, I mean, I haven't thought as deeply or as well on this thing is, you know, Nick Bostrom, who wrote a book called Super Intelligence, which is great. Maybe you've already, your listeners, maybe already know about it through you.

But I think, like, first of all, any superintelligence that exists, it's going to be a role of the dice, no matter how well thought out it is by us in the same way that you never know what's going to happen when you have a kid. No matter your genes or how you raise it or whatever, who knows, but even more so with this. But that said, I mean, we obviously owe it to our children, certainly to ourselves, to give a superintelligence the best odds of being altruistic and having it benefit all mankind rather than destroying it. And I think the best way to do that is some kind of Los Alamos level, Manhattan Project level, national, or hopefully global coordinated effort to have everyone agree and work on together relatively in the open on this project. Because I think whether it's a single government agency, kind of doing it in secret, the NSA, the Chinese government, the Russian government, I mean, who knows, any government, because it will be the security apparatus or defense apparatus. that's going to create this thing.

Or a corporate entity. You know, I wouldn't want the programmers at Twitter coming up with the ruler for the entire world. You know, it's just, that sounds horrible to me, almost as bad as the NSA, because who knows, they're just some jokers in Silicon Valley, you know. I mean, I love programmers in general. Certainly everybody I've worked with. I love it, OKCupid. I would not want the programmers at OKCupid coming up with an AI.

It would, that would be horrible. So, and I think a kind of secretive, fractured effort at creating this thing. everyone moving in parallel, racing towards a goal. You cut corners when you race. And it's something that if the wrong corners are cut, it could, it could, you know, I don't know what might happen. Yeah, we don't know what might happen. And it could destroy the world.

I mean, I don't want to sound like a lunatic. It's really hard to talk about a kind of AI apocalypse without seeming like a crazy person because of things like Terminator, you know, and, and I don't know, who knows what else, ex machina. I love, I bowl those movies. But, you know, the thing is not going to be running around doing. karate chops or shooting people with a shotgun or something. You know, that's like what a person would do.

I think it'll be maybe more painless death for everyone, but everyone will die rather than just like a couple, you know, extras. I've read a lot of places about the intermediate step, I guess, before we get to some sort of superintelligence being automation of pretty much anything repeatable, right? That if you're 21 and thinking about a career, something where you're an automaton in the sort of command and control hierarchy type company, that just doesn't make sense anymore. because machines are going to be able to do it better and more efficiently. So it seems like, or at least this is what the most common refrain is,

okay, so focus instead on creative aspects, on being the person at a frontier who creates something new and establishes it, a new niche, a new product, whatever, and then lets machines or automation handle it from there. But it sounds like if there is this level of intelligence, if creativity in some way is a reflection of our level of intelligence, and I think of creativity is just recognizing patterns. If an AI is smarter than us,

it could potentially take that to, take the creative component too. And then the question is, well, what's left for us to do? I mean, I think that question, people are going to have to answer that question even before there's a general AI, even before there's kind of like, you know,

specific AIs because, you know, I mean, automated cars are going to put millions of people out of work self-driving cars. And so, like, you know, I mean, these are automation in general is going to be a huge economic challenge and therefore social challenge, I think.

Which, you know, I would be more sanguine about if I thought that government could like, agree to get stuff done. But I think it's going to take some kind of, it's going to be a shock, I think. What do you do when there's five million people who can't feed their kids?

You know, I think there's going to have to be some kind of redistribution of because, you know, for example, if Uber no longer employees drivers, Uber shareholders are all the richer, you know, and I think there's going to have to be essentially a tax on the use of artificial intelligence that will have to end up back in the pockets of the people

that it's displaced. One of the things that I've found looking at the data is this kind of rich, getting richer, obviously everyone knows about economic inequality and actually there's been some recent changes in that data that's at least a little encouraging at the kind of wage level. But what we found is, if

look at the, let's say, profit margins of the highest profit margin companies, right? So there's always a group that's the highest margin. What's the margin of that group? That has been steadily rising, meaning more and more is accruing to the winners. And there's sort of this like magnified power law thing going on. Like you mentioned, you know, you don't want one guy somewhere that created this AI and has a massively disproportionate amount of the power influence. It seems like that's like impossible to guard against because it's so much easier to start a company to program something one person, five people. It doesn't take a corporation anymore. Well, I mean, it's not hard to guard against it if you, well, if people, if you make the right laws and people obey them. You know,

I mean, you could tax that income. I mean, you know, I look, I mean, I think it'll just be interesting to see where things are in like 10 years. If for the kind of 99, the 0.1% of the world, is it worth it to them to have whatever increment? metal dollars at the cost of, you know, living in fear of social unrest, for example, like, do we want this to be like a South Africa type situation? Not racially necessarily, but just in terms of there's certain people who live under guard all the time. And there's people who want what they have, you know, that doesn't sound that attractive to me personally. You mentioned this as a potential, you know, project of yours, you know, exploring this more,

maybe writing about it. What's your particular angle? Like, what aspects of this big question? Are you, most interested in and do you feel you know you'd have the sort of inside track on exploring you know I mean I I have an inside track on how kind of tech businesses are run and I would like to take my knowledge of how decisions are made in a in a big tech company how computer programs really get written essentially and and and maybe run through a sort of speculative nonfiction a walkthrough essentially of like how it could happen, you know. Just to make it more real. I think like Nick Bostrom's book is amazing.

It's extremely dense, as I know you know. And its power and its density also make it somewhat inapproachable for most people. It's like, you know, whatever. You know, it's very, it's very rigorously argued. And I think I would like to, you know, honestly sensationalize the ideas a little bit more. But make them not the Terminator, the kind of like Hollywood version, but like what this could really, this is exactly what could really happen, you know, for example, you know, and just lay it out and maybe tell the story from a personal level on the effects it would have, you know, what the apocalypse would feel like. I don't know, just so people, you know, when I talk to people about this, like there are a lot of people, I certainly have never heard of Nick Bostrom, never really considered the idea that the thing that's going to help them not have to drive their cars anymore, given 10 years to grow could have like grave implications for the, for the world.

and I just want to spell it out a little bit more. Like, yeah, I just got to figure out how to do it. Are there other writers in this area, Bostrom being sort of impenetrable for me, certainly, and for a lot of people that you like? Do you, are there other writers that, or pieces or essays or anything that you've read that you think is interesting and good? I mean, I thought the wait but why, I can't remember the guys.

Tim Urban? Yeah. Yeah. The wait but why, you know, super intelligence explanation, which they talk about Bostrom a lot in that book is actually pretty compelling and very approachable. You know, the singularity is, of course, a very famous book.

I've tried to read it. It's sitting on my nightstand. It's not very exciting to read. It's a lot of charts all kind of pointing up into the right in a logarithic fashion. Basically, things grow exponentially. Here's like 100 cool technologies. Right, exactly, yeah, yeah.

I mean, which is cool. I mean, you can't discount the vision that it takes to think of the stuff, but it's not a great read. For sure. I'm working through this kind of Stanford AI commission kind of white paper right now. Honestly, I would recommend. The Bostrum is worth the time if you're into kind of slightly more technical reading. The way but why explanation is really great.

If you say, you know, key inside track is understanding how big tech companies work. If you were giving advice to a 21-year-old interested in, it could be finance, it could be any of these fields that's increasingly data-centric, quantitative. What skill sets do you think have the most value, maybe are the most undervalued or even overvalued that people should focus on as they're thinking about their careers? I think, I mean, the skills that have been most important to me and what I've done is, has been a kind of real world experience. or like a sense of how people work. You know, I haven't spent my entire life in an academic department.

I've done a lot of different things. I think that is extremely helpful in analyzing data. Certainly when we were going to, OKCupid, and I assume also any data analysis in a social setting, Facebook, Twitter, aside from their advertising data analysis. But you just really, your goal is to understand human behavior, the behaviors that are generating the data that you see and the psychology that has generating the behaviors that are generating the data that you see. And some experience with people, I know this is so cliched and stupid, but you just have to be able to at least make intelligent guesses about what people want from your website,

what people want from the page, what they want from the button that you're doing, why they're doing things. Some of it is just armchair theorizing that you can't prove either way, but you've got to make decisions based on whatever conclusion your math is spitting out. And so I just think a kind of like humanistic education, reading a lot, doing a lot of different things really, really, really, really helps. Like, the math is this not that hard, you know. It's what you do with the results of the math.

It's always by far the hardest part. And, you know, like to what you said, which hopefully made it in here, is picking the right metric to manage against. You've got to do that intelligently just in case it wasn't covered. You know, at, OK, Cupid, you know, in the early days, you think of a website, you're thinking engagement, you're thinking time on site, you're thinking page views. Well, you know, it occurred to us very early on.

that like those are crappy metric for a dating site. It doesn't, you know, what does it say about a dating service if somebody is coming day after day after day after day for two years or something like this? It looks great for Twitter. That's horrible for us. You know, they're not finding a date. So we ended up having, after a lot of thought and trial and error, we ended up picking this metric called four ways, which is essentially conversations, how many separate

deep conversations are happening on OKQAWIT because that's what we want to generate. We want people talking to each other. People come to OKCupid to meet people. How do we proxy them meeting someone? and that's, they're having a conversation on our site, you know, because we don't know whether people actually meet up in person or not. And so, you know, that was a really important decision. If we had been managing towards page views or clicks or even just raw messages, our site

would have failed. Like, raw messages doesn't work because people send, might be sending all those messages just to the same handful, relative handful of attractive people, for example, and ignoring everyone else. And they're not getting responses. They're not happy. The recipient isn't happy, et cetera, et cetera. So we really had to, like, dig to create the right metric for success for us.

And I think that's because, you know, we thought about it a lot and we were able to kind of work back from what do people want out of our website and figure out a metric that we felt like could measure that the best. It seems like another way of this idea, saying this idea that what really matters is coming up with the right questions, not so much the answers. We're much better at answering stuff now because we've got tools and data. Yeah, yeah. But getting the right motivations, the right questions, the right measurables. is the search mission that will yield a lot of fruit for budding entrepreneurs, for young workers. Absolutely. And for writers, frankly.

I mean, you know, I mean, that was the hardest part about writing daticalism was, you know, asking the right questions. The data was all there. Like, I had data from Twitter, Facebook, Google, reams and reams and reams of it from OKCupid. But I had to figure out what questions can I answer. What questions should I ask? What questions would people want to read the answer to? you know, and to a degree that's always going to be the question for any author. Do you think that there's a certain type of person that's best suited to, having gone through

twice yourself, the kind of entrepreneurial startup type setting? Are there people that maybe should avoid it? Maybe the answer is a negative one that it's not for everyone? You know, I guess, I mean, I'm sure it's not for everyone, or I would imagine. I've worked with the same group of three other guys both times. and things have turned up very well both times. And so I don't know the failure case, luckily enough, you know. But I think there is a lot of luck involved.

I think me, my co-founder, Chris Coyne, talk about all the time. Like, we're smart guys. We worked hard. Things got to gone sideways very easily, you know. And so I wish more entrepreneurs would recognize the amount of luck that has gone into their success because there's a tremendous amount. That said, I mean, somebody who, the way to position yourself best for success

and inherently, in the big crapshoot that is starting your own company, I think you have to be willing to try a bunch of stuff. I think people, I mean, obviously there's counter examples, but people who doggedly stick to the same idea regardless of whether it works or not. I think that's a recipe for disappointment a lot of the time. I think you have to be flexible.

We try to all kinds of garbage at OKCupid through the, you know, we started that company in 2003. We weren't even really a thing until 2008 or nine. So there were some real lean years for us. You should be extremely persistent because we held on through all the lean years, but you shouldn't be too beholden to a single idea in your persistence. You know, be committed to the idea of having your company, but don't necessarily be too committed to, you know,

this one match algorithm that you swear is going to work or that people are going to love, you know, or this one idea of bringing people together, just use a dating example. It's one idea of how dating should we, work in defiance of whether people like it or not. You've got to keep an open mind and you've got to be able to listen to the data that's coming back. You said that OK, Cupid's growth was not this kind of classic massive exponential ramp up growth that people hear about in the most famous startups, but was much more kind of linear, slow, and steady, and that there were those lean years.

How do you know, or how did you know, and maybe it was just pure persistence, whether or not something was worth continuing to pursue? I mean, were there times in that, in those, early years when you guys discussed, well, maybe this just isn't going to ramp in the way that we wanted it to? Sure. Yeah. I mean, you know, we didn't know. And that's the hardest thing is, like, that is the hardest part about being an entrepreneur,

I think is when your idea is doing okay. When it sucks, hey, walk away, you know, obviously, shut it down. When it's great, when you've created Facebook, only an idiot would not realize that that's going well, you know, and that you've hit a home run and would not want to stick with it and hire a bunch of people and really throw themselves into a nascent Facebook. You're right? But what do you do when things are like, all right, you know, I don't know if it's really going to be successful. Like we're stable now, but it's not stable long term.

I might be wasting my time and my money. That's very hard. And that's, it really helped. There were four of us that were friends. If it had been one person, even maybe just two people who had started OKCupid, I don't know if it would have lasted through those times because it just, certainly for one person, no way. Because you're just like, eh, you know, I'm just going to go get a job. you know what was what was the division of labor and maybe skill set like amongst the co-founders

you said there's four right there's okay cupid so so how much overlap was there in like responsibilities and skill set and how did that get how did that shake out very little overlap at any given time in terms of the roles people were filling I think we do have some actual overlap in kind of core skills I mean for example like I worked primarily on the editorial and the kind of product and the viral content marketing, you know, aka the blog and a few other things, until about 2011, at which point I basically became the CEO of the company for the last four years and ran. I just dealt with a P&L and did almost nothing traditionally thought of as creative, you know.

But among the founders, you know, Chris Coin and I, to a much lesser degree, Chris would work on the product, he would do the front end, he would come up with the kind of ideas of like what feature is going to be on OKCupid, what feature should we try? Max Crone was, is a fantastic programmer. He wrote all the back end, made it scalable, made it work.

Without him, there would be no code to put a front end for Chris to put a front end on. Sam Yegan was the CEO before me, and he later became the CEO of the entire match enchilada. He's an amazing negotiator, a business person, he did the things that you think of a CEO is doing. And so we never really stepped. Chris and I were most similar in our roles. Like we both kind of worked on the content and the things that the users would actually interact with. We have a great kind of professional relationship.

You know, Max definitely had his own single domain. Sam definitely had his own single domain. And that helped a lot because that way we weren't arguing over who was better at X, Y, or Z. And, you know, you don't know how to do this. Or, you know, we've definitely respected those fences between our roles. And that was very important. Obviously, it seems like one of your key advantages is the creative side, right? In writing and music and the blog for both Spark and OKCupid, what was it like being the more traditional CEO in contrast to, you know, those more... I mean, it was interesting. You know, I became the CEO of OKCupid. Kind of after the blog had run its course, I already had my, I was already working on my book.

So I felt like creatively I kind of did what I would ever have wanted to do with OKCupid's data. and that whole scene, you know, and I had a creative outlet, i.e. the book. So, and business is creative in its own way. You know, I mean, I had to figure out how to take our P&L, which at the time I took over was, you know, say we were making, I think I took over in mid-11 and I think our final EBITDA for that year was like six million bucks. Like, you know, match bought us earlier that year because they wanted a lot more out of it. And, you know, the year I left, I think, I made close to 40. You know, it was like a cool challenge to take, especially to take the, the principles of how to run a business that matched new very well, sometimes to their own detriment, but they knew very well, and lay that over OKCupid, get the employees

to buy into it, and lay it over the website in a way that the users didn't find off-putting. So it was cool. I enjoyed it. It was weird, for sure. I mean, I had definitely not ever discussed any finer points of accounting or any, you know, org charts and none of that stuff. I didn't know any of that stuff when I took the role, which, of course, I was promoted to because I was a founder and it's just like what I needed to do at the time. How many employees was it at when you left, let's say? When I left was maybe 32, 34, 35,

something. That's a pretty small organization. So you know, everyone, yeah. Yeah, yeah. You mentioned, you know, a book being an ambition potentially on this kind of nonfiction narrative around AI. Any other entrepreneurial seeds kind of brewing in your head? Um, you know, I mean, I was, like to do something, one of the things that we all really liked about OkCupid and one of the reasons that we started that business as opposed to like an ad network or something, you know, in 2003 was that it created like some kind of like positive real world outcome. You know, people are falling in love, having sex, whatever, you know, based on what we were doing as a business, you know, and the business's goal was to make more of that happen in the real world, you know.

And so we really liked that and we could have, you know, whatever, we were all good with computers, we were all math people, we could have started some kind of like, you know, in an ad network or some other kind of thing and probably made a lot more money. And I would like to stay true to that idea to create some kind of like positive real world thing. I'm a little tired of the internet at this point, you know, been through. It started at SparkNotes in 99. That's like the first bubble, pre first bubble, you know. I've kind of like been through all that. You've done that? Yeah, a little bit, you know. Again, some of it I haven't done very well and there's been a lot of luck through that the whole time. but yeah, I've done that.

So, yeah, I don't know. I kind of, I'm kicking around a few ideas. I'm really into farm animal welfare, animal welfare in general, just personally. And I would love a business, whatever I work on to reflect that or increase that. What's the background there? How did that become a passion? I mean, I'm just, I don't know. I mean, I've been a vegetarian for a long time.

This is my wife. So is my daughter. It's just something I've thought about a lot. You know, actually, I really liked Jonathan Saffafer, Forres, eating. animal's book. I was kind of already on board before that. I imagine most of his readers probably were, but like, you know, I thought that was a great way to talk about it. And I feel like it's like, you know, it's really hard to talk about this without sounding preachy. But I feel like it's like a weird, it's, it's, it's one of the most notable inconsistencies in most people's lives, I think, is how they

treat animals. Like lots of people's have pets and love them and then yet pay for people to torture. very, very similar animals just right down the road and then eat them, you know? And so it's just an interesting thing to me, the way people treat animals. And I since become friends with this guy named David Come and Heidi. He runs this nonprofit called the Humane League that I really love how they do things and talk to him more. So I've just kind of like, you know, whatever, I've just bought into it. Everybody's got their ideas.

Very neat. Are there other entrepreneurs or budding companies? We've talked a lot about writers and books, but other ideas that are being acted on or in the early stages of being acted on that you're following with interest or appreciate today? Well, I mean, two of Chris and Max from the OKCupid team, they started this company called Keybase,

which is this kind of attempt to make essentially unbreakable cryptography accessible to everyone. You don't have to understand PGP or one-way functions and hashes and all this stuff to make sure your documents and your communications are completely private, you know, from Apple, from Google, from Iran, from the NSA. And it's a really hard problem, actually, because the math and it requires complexity. And so it's a very hard problem to essentially hide that complexity yet make it actually work. So they've been working on that. It's called Keybase. It's really cool.

I'm an investor, full disclosure, but I think it's interesting regardless. Yeah, I mean, there's a variety of kind of smaller companies that I think are doing cool things. Yeah, I mean, there's, I work a little bit with this company that's trying to make online eye tests. So you, you know, so you don't have to go to the ophthalmologist to, like, figure out that you can't see or get your prescription. I think that's, like, a pretty cool idea. I don't, I guess I don't really follow, I'm not really a big, like, entrepreneur, seamster, you know, too old. But yeah, I mean, I don't, I try to spend as little time as possible,

though I check my phone as much as anybody else, but I hate myself every time I do it. I try to spend as little time as possible like screwing around on the internet because it, you know, it sucks up a lot of time, you know? And I want to set a good example for my daughter. You know, I'm not like the world's biggest tech enthusiast, I guess. Right. So thank you so much for all the time today. And hope everyone enjoyed the talk.

Yeah, it's my pleasure, man. I had a good time. Hey, everyone. Patrick here again. To find more episodes of InvestorField Guide.com forward slash podcast. If you're a book lover, you can also sign up for my book club at investorfieldguide.com forward slash book club. After you sign up, you'll receive a full investor curriculum right away and then three to four suggestions of new books every month. You can also follow me on Twitter at Patrick underscore Oshag.

OSHAG. If you enjoy the show, please leave a quick review for us on iTunes, which will help more people discover Invest Like the Best. Thanks so much for listening.