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Attention is scarce.
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If you 📍 don't do the prep, you'll be just as bad as anybody else who hasn't done the prep.
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I think that when you try to be too performative, it just comes across as fake.
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I think curiosity is definitely a big thing there.
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I think listening, as you mentioned earlier, is a big skill there.
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I think another skill maybe is the ability to come up with counter arguments on the fly.
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People really don't understand that if you really could just look inside someone's mind, they're not thinking about you, they're thinking about them!
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Some of the most important scent of discoveries in an entire century happen by one person in one year, and that's really mysterious.
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I've only discovered a thousand ways not to make an electric light bulb.
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That's information via negativa.
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Why do these luminaries tend to have these incredibly concentrated periods of productivity?
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Babe Ruth is reputed to have said "There's just no beating the fella who will never give up" if you do everything and I mean everything, you will win Jim O'Shaughnessy: Hi, I'm Jim O'Shaughnessy and welcome to Infinite Loops.
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Sometimes we get caught up in what feel like infinite loops when trying to figure things out.
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Markets go up and down, research is presented and then refuted, and we find ourselves right back where we started.
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The goal of this podcast is to learn how we can reset our thinking on issues that hopefully leaves us with a better understanding as to why we think the way we think and how we might be able to change that to avoid going in infinite loops of thought.
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We hope to offer our listeners a fresh perspective on a variety of issues and look at them through a multifaceted lens — including history, philosophy, art, science, linguistics, and yes, also through quantitative analysis.
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And through these discussions help you not only become a better investor, but also become a more nuanced thinker.
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With each episode we hope to bring you along with us as we learn together.
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Thanks for joining us, now please enjoy this episode of Infinite Loops.
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Jim O'Shaughnessy: Well, hello everyone.
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It's Jim O'Shaughnessy with yet another Infinite Loops.
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As this show gets a little more popular, I am getting cooler and smarter and really switched on people as guests, which is great.
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However, what do I do when I get a guest whose name is Dwarkesh Patel, who hosts the Lunar Society Podcast, and here's what's killing me, has been called one of the best podcasters alive?
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You've interviewed luminaries.
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Your approach to planning for a podcast is almost like doctrine. It's almost a canon.
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And I'm reading all this.
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Luckily I have a very smart person who prepares much of this for me.
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And all I did was go, "gulp. ” Welcome. How are you?
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Dwarkesh Patel: I am good.
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And I'm a huge fan of your podcast.
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And to have you say nice things about mine or have you read them is extremely flattering.
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But I would not accept that characterization when I'm in the presence of the host of Infinite Loops podcast. So...
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Jim O'Shaughnessy: Yeah, that's great. Dwarkesh Patel: ... a huge fan. It's a privilege. Jim O'Shaughnessy: Yeah.
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Well, the privilege is mine.
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So let's start out with podcasts.
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I always joke that I do everything wrong, pretty much.
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I mean, this is kind of my indulgence, and I just have this great privilege to be able to talk to really smart people like you.
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Honestly, I read all of your stuff, I listen to the podcasts, I take notes, but I end up kind of riffing off of those.
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I always write them out ahead of time.
2:59
That's what I was doing for the last couple of hours.
3:02
Going through your stuff so it's fresh in my mind.
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But then I try to keep it, I don't know, give and take.
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Because when somebody says, "We'll cover that later."
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I learned this from my son.
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He said, "No, no, no, no, no.
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When they say, “We'll cover that later,” stop them and say, “No, let's cover that now." Dwarkesh Patel: Yeah.
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Jim O'Shaughnessy: So what do you think?
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Is there a way to train people who are aspiring podcasters to be better?
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Dwarkesh Patel: That's an interesting question.
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I'm curious what you think about this as well.
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I'm curious how you think about how you've changed as a podcaster.
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But in my experience, this is not...
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I don't know if this is something I've gotten better at.
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I think it's just that it just takes a lot of prep, and if you don't do the prep, you'll be just as bad as anybody else who hasn't done the prep.
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And if you do do the prep each single time, no matter how far deep in you are, each single time, it'll require days, if not weeks, of effort.
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But maybe there is a skill to it, maybe there's a judgment of being able to think about which questions are good, which will get you actually new information.
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When are you just asking a question that will result in a dull answer or answers they've already given elsewhere.
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But I'm kind of curious how you think about this.
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Is this something you can improve at?
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And how have you changed over the years?
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Jim O'Shaughnessy: So I love this.
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I joked on Twitter before I came on. I said, " He's so good.
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I'm just going to let him interview me."
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And so I prepared for this, my friend. So how have I changed?
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I think that I have changed in my ability to listen very closely to the answer that is being given.
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And then I'm lucky in that if I read something, especially if I write something out, I have pretty total recall of what I wrote out or read. And so I let those...
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If I hear something really interesting that sparks a bunch of other associations, then I have gotten better, I would think, because I learned to listen more closely.
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As you know the old saw, "Many people listen, not to listen, but to answer."
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And so I improve that skill, I think.
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And then I completely agree with you on prep, by the way.
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I'm a huge reader and enjoy doing it.
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And when I come across things like the thing that kind of made you go viral, which we're going to talk about in a minute, I'm like, "Ooh, okay, so here's somebody I might want to have on the podcast."
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Then I kind of do a deep dive.
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And then I'm incredibly blessed to have a team that literally writes novels in terms of the entire oeuvre that you have.
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And so I look at those usually the night before, and then I take notes on my thoughts about what my colleague Ed is writing.
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He's a superb writer, a recovering lawyer.
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And so I think that that's probably what has made me, if I've improved at all, improve. How about you?
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Dwarkesh Patel: Yeah, I actually had a pleasure of talking with Ed and getting his advice on the SBF interview I did. So he's fantastic.
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It was a pleasure to work with him.
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But yeah, I've been reading the Lyndon Johnson biographies that Robert Caro has compiled.
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Jim O'Shaughnessy: Oh, those are great.
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Dwarkesh Patel: And there's a line in there where Lyndon Johnson early in his career is teaching these Mexican students in the south of Texas, and he tells them, "If you do everything, you will win."
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And I think this is the right approach to have to, I guess maybe all jobs, but especially to something like interviewing.
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But we never really know. Are you done? You've read their books.
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Okay, maybe that took you a week. Are you done yet?
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Well, maybe you should read books that are rebuttals to the books.
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Maybe they're different perspectives.
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Maybe you should read other commentary on similar subjects.
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Maybe you should read associated papers.
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Maybe you should listen to every single interview they've ever done. Are you done now? Maybe not.
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Maybe there's still more to do.
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And if you do everything, you will win.
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But have you done everything?
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So it is kind of a daunting prospect of you never know you're done. Right?
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It's not a task where you know you've reached...
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you've done everything you can. Jim O'Shaughnessy: Yeah.
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And that reminds me of my friend, David Senra, who does the Founders podcast.
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I don't know if you've heard David, but he is a maniac. He's my kind of maniac. He's single format. He never has a guest.
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Each episode covers a founder that he is fascinated by, but his do everything, is literally do everything.
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In other words, he reads every book. That's what he does.
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And he takes notes, copious notes, goes back and forth between the book and the notes, and then he generates a script.
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And it's not one that he...
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He might write it out, but he ad-libs it after writing it out. And he talks...
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I mean, the static-to-noise ratio of his podcast and wisdom, like no... Well, not no noise.
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Mostly signal, lots of wisdom. But he's crazy. I mean, but it's great.
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That's because that's what he does and that's all he wants to do and be.
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I think it can get a little more difficult with people like us, or at least with me.
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I have a ridiculous number of interests that I try to stay current on.
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But as you know, the newest articles.
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Let's take AI for example.
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I'm the chairman of Stability AI, which is an open AI company.
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Wow, talk about jumping into a deep end of a pool with no life preserver. But I enjoy that.
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So it's kind of fun for me.
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And that actually is going to turn to my next question.
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Is there a natural disposition, do you think, to people who end up being good at podcasting in that, I love diving down rabbit holes, for example, and I've always been voraciously curious and you seem very much like a similar type person.
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What do you think about that?
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Dwarkesh Patel: Yeah, I think curiosity is definitely a big thing there.
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I think listening, as you mentioned earlier, is a big skill there.
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I think another skill maybe is the ability to come up with counter-arguments on the fly, or at least prepare them in advance.
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Because one of the ways you learn a lot about somebody or their ideas is about criticizing them and having all the counter-arguments ready so that you can offer them up.
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I'm just thinking back to, I had this guy on my podcast a few weeks ago who's probably the main proponent nowadays about Georgism, which is the idea that you should tax only land and nothing else.
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And there's really interesting economic argument of why you might want to do that.
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But then you had go through all the economics of why this is the case and why this might be a bad idea.
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And you have to have every single counter-argument ready.
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And I think this teaches you a lot about the ideas you're debating on the podcast actually, or discussing, I mean.
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Because really when you're reading a book, usually a lot of it just like goes in one ear, goes out the other.
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Or I guess goes in one eye and goes out the other.
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But when you're forced, because you know you're going to talk to this person, you're forced to come up with, how could this be wrong?
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What would I ask them that would really test this assumption, really test this premise?
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Then the amount of learning you can get out of that...
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And I don't know if this is your experience as well.
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The amount of learning you can get out of that is just exponentially more than you can get otherwise.
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Jim O'Shaughnessy: It is my experience.
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In fact, one of the things that I instruct everyone who's helping on the podcast, but also in O'Shaughnessy Ventures more generally, is I am a huge believer in steelmanning the opponent's argument. Strawmanning is so lazy. Dwarkesh Patel: Yep.
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Jim O'Shaughnessy: And I had one of my colleagues tell me, "I think you might be assuming more switched-on status for the people.
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They might not even know what a straw man is."
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And I went, "I think we have to go after this like everyone listening to us does know what a steelman is."
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And then when we look at the profile of our audience, because this is a very quirky podcast, guess what?
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Every single one of those people in that profile knows what a steelman is.
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And more importantly, appreciates the benefits, as you've just said, of being able to learn.
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Because I couldn't agree more that a clash...
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Look at the language we use.
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I always try to be really careful.
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It's not a clash, it's a discussion.
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And hopefully both you and your conversant are trying to learn better things, iterate better. How do we do that?
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We do that by learning from taking on challenging things that we might not agree with then steelmanning those things.
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And then listening to the domain expert.
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So huge, huge fan of that.
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Have you ever had that go wrong?
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Dwarkesh Patel: I think it's harder to do when you have a technical guest.
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Last week, I interviewed Ilya Sutskever, who is the co-founder and chief scientist of OpenAI.
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And it's hard, obviously.
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In many cases, you can learn enough about the field to be able to think about how might this person be wrong?
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What are the best counter-arguments?
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When you're talking to somebody who is basically one of the founders of deep learning and has come up with most of the revolutionary ideas in the field, you should really not assume that you're going to come up with something on the fly that is really going to disprove their assumptions about AI or anything.
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So in that case, I think the sort of Socratic attitude of coming up with counter-arguments might not work as well as you might expect.
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So in that case, it's just kind of interesting to get their broader takes about where they see the field of AI going.
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Give them the opportunity to say, "If you had to look back on OpenAI 30 years from now and you saw that maybe not that much progress has been made in the field of AI, how would you explain it looking back on it?"
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Give them the initiative to come up with their own counter-arguments, right?
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So yeah, it does work better in cases where it's a field that you can easily approach and come up with the counter-arguments on. Jim O'Shaughnessy: Yeah.
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OpenAI is a competitor of Stability AI, obviously.
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But my guy over there that I'm scheduling a podcast with is a fellow named David Ha, who is a mega genius at AI, especially at training models.
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He literally joined us without being recruited from Google Brain.
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And what I'm planning on doing is really just trying to turn it into a masterclass on AI from David, and I'll just play the supplicant.
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And I, maybe, might know a few of the questions that might get us off into a good conversation.
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But what my goal with that is is to appeal to a slightly broader audience than just AI domain experts.
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I kind of view my role at Stability AI, and we're going to talk about intellectual marketplaces in a little bit.
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But as in socializing and amplifying the conversations because I think they need to be had.
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And there are a lot of people who don't really understand AI well.
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They're frightened about it.
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And I don't think these are illegitimate concerns.
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And so by taking them seriously and engaging in the conversation, I think that that's helpful to help other people get tuned in to what's really going on.
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Have you ever found when you were doing an interview with a guest where you just found yourself seriously disagreeing with them?
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And how do you handle that?
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Dwarkesh Patel: It's interesting because if you really think about what is happening in a disagreement, what you really want to do is you want to get to figure out where is the place where you just have incompatible assumptions or premises.
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And often what ends up happening is you just kind of talk around each other and you never really realize what you're disagreeing about.
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So the key I think, is as soon as possible, just figure out what is it exactly that you're disagreeing about.
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And oftentimes, this must be your experience as well, you realize that you actually don't disagree.
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You're just saying the same thing in different ways. Jim O'Shaughnessy: Yes.
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Dwarkesh Patel: And how do you resolve that?
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I think at some point you just had to let it go.
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You have an hour or so to do the podcast.
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If you've identified this is where we disagree, we know why we disagree, we just are not going to resolve this fundamental mismatching world views in the next hour, then it's fine to move on.
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But until you've done that, until you've identified this sort of, I mean merge conflict, if you're going to use the computer science lingo, it is good to harp on that until you know what is the crux of this debate.
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Jim O'Shaughnessy: Yeah, I think that's right.
17:29
And I agree completely on the idea of, you might be saying the same things, but in different language, so to speak.
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And back in the '70s, there was this newish thing called neurolinguistic programming.
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Richard Bandler was the champion of it.
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They wrote many, many books about it.
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What I really took away from doing a deep study of it was this idea that people literally communicate differently.
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And if you take Tim Leary and Robert Anton Wilson's theory of reality tunnels, you basically are saying, "Oh, okay.
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So their perceptions are leading them into a different reality tunnel than my own.
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Let's see how we can communicate better."
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But on NLP, not natural language processing for our computer friends, but neurolinguistic programming, one of the things that really stuck with me was people communicate differently.
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So most people it turns out are visual communicators.
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So when you would say things like, "Can you see the big picture?
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Does this graph make sense to you?"
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They're very graphically oriented, et cetera.
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If you say to them, does that ring a bell with you?
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They literally will not hear what you just said.
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It will be like bell, bell, and they'll see a picture of a bell, they'll see it in a visual format.
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But I found that if you just listen for maybe the first five minutes, you are going to have a clue as to how your conversant communicates.
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So auditory is next most popular.
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And then the other one that I really had to learn to get better at, because I'm visual and auditory, I'm kind of a mix of those two, but kinesthetic.
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Many people are kinesthetic communicators, and therefore you would be doing, are we vibing here? Do you feel what I mean?
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All of those types of things.
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And one of the things that I really found after I practiced that is it makes a huge difference.
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You can literally watch your partner in conversation relax, become much more open with their body language.
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And that's always I found to be really a cool thing.
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Now, I don't know if the books are still...
20:06
You're familiar with neurolinguistic programming?
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Dwarkesh Patel: I am not.
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But the idea you mentioned, or just leading off from what you said is really interesting.
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I mean, if you read these biographies of great scientists, it's kind of interesting that they have often similar ways of coming up with and thinking about problems.
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I'm sure you've seen this stuff about how Einstein's great theories came out of these thought experiments where he was just a brilliant visual thinker, and he could come up with these thought experiments that clearly illustrated the problems or the existing way of thinking about gravity or other concepts. And it's interesting.
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So I'm a programmer and sometimes I talk to my programmer friends about, "When you're thinking about a problem, how is it that you think about it?
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If you see a program, what do you think?
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How do you reason through what's going to happen once you run it?"
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And some of my friends say, "Well, I just kind of logic my way through it."
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And some say, "Oh, I actually see the visual of what's happening in this for loop, or in this if statement.
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I actually see that visually that sort of changes in these values and in the flow of the program."
21:16
And it's really interesting how differently people will approach the same problem.
21:19
And you don't realize when you give somebody a problem that they've just come up with a solution in a completely different way.
21:25
Their mental hardware, the way it processes that problem, or the software, it was just a completely different interface there. Jim O'Shaughnessy: Yeah.
21:34
I had the honor of meeting Seymour Cray, who created the first supercomputer.
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And when I went into his office, this would've been the mid 1980s, I was a kid.
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And on his desk were a series of yellow legal pads.
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And so as I saw them, I'm like...
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It filled with formulas, with everything else. And so I asked him, "Dr.
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Cray," and just pointed at him.
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And he goes, "Oh, that's how I designed the first supercomputer." And I was like, "Okay."
22:13
What do you think about that?
22:16
I mean, it seems so foreign to me now with all of the stuff I'm dealing with at Stability and whatnot, but you're the domain expert.
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Dwarkesh Patel: Oh, no, not at all.
22:26
I mean, you know far more about this field now than I do, given your centrality in it now.
22:32
There's these stories about how in the '90s, and they did thousands, computer science professors would force students to write out their programs.
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They couldn't program them in.
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They'd write them out because they wanted to make sure that they could conjure up the semantics of their programming language without the aid of the computer.
22:52
And we don't do that nowadays because we realize that why not use the help the computer gives you.
22:57
But I think there is something interesting to that idea.
22:59
I'm sure you've heard the quote by the famous computer scientist, Brian Kernighan, where he says that, "Computer programs are written by humans for other humans to read, and only incidentally for computers to execute."
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Jim O'Shaughnessy: I love that quote.
23:13
Dwarkesh Patel: Yeah, yeah. And it's interesting.
23:18
That's kind of the attitude I try to bring towards my podcast, where this conversation is between a host and a guest for the pleasure of the people participating in the conversation, and only incidentally for the audience.
23:30
Jim O'Shaughnessy: Right. Dwarkesh Patel: Yeah. Jim O'Shaughnessy: Yeah.
23:33
And that's really insightful because I think that one of the things that does draw me in is that exact notion.
23:42
In other words, when people would ask me, " What are you going to do with this Infinite Loops?"
23:48
I would always ask them, "Have you ever seen the movie ‘My Dinner with Andre’?"
23:48
which was a 1980, and I think with Wallace Shawn, who was made famous by ‘The Princess Bride’ of all things.
24:00
He also happens to be the son of the legendary editor of The New Yorker.
24:07
And so yeah, deep literary background, super smart guy, but a good actor too.
24:13
The point of ‘My Dinner with Andre’ is literally that's what it is.
24:20
They film the two men having dinner together, having disparate conversations that are very desultory in that they'll go from one topic to another.
24:30
And it absolutely is riveting.
24:35
I actually rewatched it before starting this, and I'm like, "That's what I want this to be like."
24:41
I want it to be like somebody just sitting at the next table like, "Ooh, and this is interesting.
24:48
This is an interesting conversation."
24:50
And so the performative aspect of it seems almost less.
24:58
I think that when you try to be too performative, it just comes across as fake, right? Dwarkesh Patel: Yeah.
25:04
Jim O'Shaughnessy: Like all those TV pitchmen of...
25:06
Well, you probably are too young to remember them, but they used to...
25:12
Dan Aykroyd did fantastic stand-ups of them on SNL live, and with the cheesy suit and the "But wait, there's more."
25:23
And the entire faked energy levels.
25:28
I always was amused by that.
25:31
How does your approach, because you're also a great writer.
25:35
As a matter of fact, that's how I discovered you, was your piece, ‘The Mystery of the Miracle Year’.
25:44
How does your preparation for the podcast differ from your essay writing?
25:49
Dwarkesh Patel: That's interesting question.
25:50
I think there's, you know what's interesting?
25:54
I think with podcasting you have a lot more latitude to try things out because you're not, when you have to write about a topic, you had to defend a thesis, you had to come up with some idea and you have to say, go through all the angles.
26:08
You got to make sure, is this something I really believe?
26:10
Do I have good evidence to believe this?
26:12
And with the question you're just like, "That's an interesting idea.
26:14
That's an interesting thought."
26:16
And you can just ask that.
26:18
And if it doesn't work out, it doesn't work out.
26:21
But sometimes since you're talking to another person, they might have a super interesting idea there that you would've not discovered if you hadn't just asked a weird question that you would never write about. But you know what?
26:35
I had a similar question for you actually, not about writing and podcasting, but I wonder about the, how the effort between investing, you're like a legend in investing, but from your book it's even like a lot, you have these amazing tools about how to think about how to invest in public companies.
26:54
And more recently you've been investing in these early stage startups.
26:58
I'm curious, how does the effort of trying to determine what is the value of a public company differ from a private company that maybe doesn't have that much revenue?
27:06
They're early on, it's more of an idea and more of the people involved in the project.
27:11
Jim O'Shaughnessy: So public investing I think is sort of a great use case for empirically based algorithmic type securities. Dwarkesh Patel: Right.
27:26
Jim O'Shaughnessy: And therefore over there, that process worked pretty well for me over my career, primarily because, not because the formulas that I wrote were that much better than other quantitative investors, more to the point of a deep understanding of human behavior.
27:50
I say often that markets change millisecond by millisecond.
27:57
Human behavior has barely budged millennia by millennia, arbitraging human nature is your last sustainable edge.
28:05
So I view the algorithms and whatnot.
28:11
Listen, I've sold the company and I'm no longer there, but I left the best research team I've ever had the privilege to work with.
28:20
We're always trying to improve our algorithmic approach, et cetera.
28:26
When other people research stocks we're researching stock selection models. So that continues apace.
28:35
But ultimately I found, at least in my career, having lived through many, many pretty severe crises, it comes down to the ability to remain quite calm and have the faith in the process that you are using.
28:55
And I think one of the only ways in public markets that I could build that faith was to see the evidence.
29:02
I was not satisfied with a three-year track return.
29:08
In fact, investors listening, three-year track returns are the worst thing you can look at because your human OS is going to be delighted by the one who's at number one or two and is going to look at the one at bottom of the list and think, "Why is this guy even still in business?"
29:26
But there's a reason behind that.
29:29
It's called hyperbolic discounting.
29:32
And when you shorten your time horizon, you're literally, your thought processes change and they become, even without you being aware of it, which is the real killer back to human OS.
29:45
So in public markets, I was quite satisfied with that approach.
29:50
In private markets in which I have been investing since 2006, so not my first rodeo here.
29:57
I mean, it's the first place that the public sees me doing private investing because this is my new gig.
30:07
But private markets are much more about A, the underlying thesis.
30:16
Does this thesis make good sense to me?
30:21
If I can get my arms around, create a steelman of my own point of view, if I'm creating a really bad steelman, then that gives me the pause to think, "You know what?
30:33
I don't think I'm quite ready.
30:34
Even if I'm going to miss some big 10 Xer here, I'm not ready because I can't write out a good steelman for the thesis that I kind of sort of seem to believe, but my writing is calling me a liar." Right?
30:49
And then the next of course is people in early stage organizations.
30:57
Big companies, why they die.
30:59
Recent article I just read before we came on, on why big companies die so quickly or so often would be a better term.
31:09
I think that there is a step change when you go from a startup where very few people are wearing many different hats and the information that you're going to be able to derive from deep conversations with them, due diligence on them is going to be of a nature to inform you as to, okay, are these the right people?
31:38
And a big company, big companies become complex adaptive systems. Right?
31:43
So our immune system is a complex adaptive system and they exist everywhere in the world.
31:49
But at the smaller level of a startup, you have the bandwidth to talk to the key people at length and in depth.
32:02
And if you've written a reasonable steelman for your thesis, if the people impress to the level of, "Yeah, these guys are, or women are going to really be able to execute against this."
32:20
Because that's the third danger.
32:23
Ideas are great, but ideas are a dime a dozen.
32:28
And the fact is that a big company tried to buy me before I published ‘What Works on Wall Street’, and they wanted to keep the book not being published.
32:38
They wanted to keep it as proprietary data.
32:42
And I'm like, "Guys, you got this all wrong.
32:45
We could scream these ideas from every microphone we have access to and it wouldn't matter because human OS." They'll love us. Dwarkesh Patel: Yeah.
32:55
Jim O'Shaughnessy: We're doing well right now.
32:56
They'll hate us and say, "Oh, O'Shaughnessy was wrong about that" when we're doing poorly.
33:02
So then it gets over to, okay, great thinkers, deep domain knowledge, can they execute?
33:11
And what I've found is I spend a lot more time on asking questions around execution than I do around the thesis.
33:22
If I've built the steelman myself and my colleagues and we've chatted about it and the people seem good, then we start focusing on the people.
33:34
I'm not terribly interested in the normal metrics that most VCs always bally who about.
33:46
I think that if you've got the ability to see kind of end state.
33:53
When I start thinking about this a long time ago, I put it in my own terms, which is helpful I think for me.
34:00
And it's kind of like, well, how did they met?
34:04
What was the experience of a very rich person in say London in the late twenties, 1930s?
34:12
Because I thought with the technology that we have enabling us, we could recreate these for everybody.
34:21
And so what did they have?
34:23
They had their own car and driver, Uber. What did they have?
34:29
They had summer homes in beautiful places, Airbnb.
34:34
But the one that struck us very directly was they had their own asset manager who managed the portfolio expressly and just for them, Canvas, which is the reason why Franklin Templeton ended up buying O'Shaughnessy Asset Management.
34:57
So I kind of go through that process.
35:01
But I also, and I can't help it, I've trained myself to build algorithms in my head.
35:07
I'm building one about you right now and I can't help it. And so I do that.
35:15
And so I guess if I get to get a little extra insight, again, time will tell how dumb or wonderful this sounds five or 10 years from now.
35:27
They're putting all these things up on Twitter, "Are you a new and the best VC?"
35:32
And I'm like new and best, they don't go together.
35:37
If you're new and you don't have any track record, how do you make the claim that you're best? Dwarkesh Patel: Right.
35:43
Jim O'Shaughnessy: And I always kind of put it through those ways of looking at things.
35:51
And then I also try to just think, okay, if this comes up absolute zero, I just totally shit the bed, what do I think ahead of time?
36:02
I try to do a pre-mortem about the death of the adventure.
36:10
Because I think as my friend Jeremiah Lowin says, if you make old mistakes that has an ROI of zero, if you make novel mistakes, the ROI is super high.
36:23
And so I always try to game out what is going to be the downfall here.
36:30
I'm usually wrong, but it's helpful because it also guides the questions that I ask the founders and importantly references.
36:42
The final thing I will say is I have trained myself to really deeply and truly understand that the market is vastly smarter than I am.
36:56
And if you want to look at somebody who's lasted in public markets for a long time, what you're going to find is humility has been beaten into them by the market.
37:11
And if they haven't had that ability, if they're still incredibly arrogant, then they are a real outlier because the thing that I've learned is market's smarter than I am.
37:22
So a great signal that I look at is, I was just talking to a potential pre-seed this morning and the thing that I jumped on immediately was, oh yeah, we kind of did this just for our own fun, our own edification.
37:40
And then I put it up on Twitter and my DMs the next morning there were 500 DMs. Dwarkesh Patel: Wow.
37:47
Jim O'Shaughnessy: So will you do this for me?
37:50
I'll pay any, I'll pay you this, I'll pay you this.
37:53
That is the market screaming at you.
37:57
I love opportunities where the market, even before the thing is built, is screaming at you, "Please build this, please do this API, please make this app."
38:10
And two of the recent deals, one we've concluded, one, we're just at the beginning of stage, but that was the key.
38:21
The market in both cases, very different business plans, but in both cases, market was screaming at them and they simply obliged.
38:32
Dwarkesh Patel: You have product market fit before you even have a product. Jim O'Shaughnessy: Yeah.
38:37
Dwarkesh Patel: It's funny.
38:38
You know what's funny, the thing you mentioned about being able to in advance, map out all the ways in which you might be wrong, in which this investor might go to zero.
38:47
I actually had Marc Andreessen on the podcast recently, and I just asked him directly like, "Let's say 16Z has bad returns for the next 10, 20 years. Why would that happen?
38:56
How would you explain that looking back?"
38:57
And I think that he had a pretty thorough answer to that.
39:02
And I think that is a good sign.
39:03
If you met somebody who is handling a lot of money or getting a lot of money, but that could not imagine that going wrong, then that's a bad sign and they haven't thought through all the ways in which the world might throw something at you.
39:17
Jim O'Shaughnessy: Bingo.
39:19
And that itself becomes like, I'm a huge fan of Claude Shannon and information theory and what the true nature of information really is.
39:28
Basically, it's something really new that presents itself.
39:33
I can't remember whether it was Corvinsky or Shannon himself saying basically a poem contains a huge amount of information.
39:44
A political speech contains zero, right? Dwarkesh Patel: Right.
39:48
Jim O'Shaughnessy: And it's a great way of looking at it.
39:50
And Marc's a super smart guy.
39:53
And one of the things that I do, again because of my training is we used to, because we have the ability to look at our strategies performance over a variety of market environments, one of the things I did when I still was taking money directly from the end investor, the rich person, we would let them come to our firm directly.
40:18
What I would do is I would come sit down with them and they invariably were coming in asking for whatever our hottest strategy of the moment was.
40:27
And so I would put up on the screen, great that you're interested in that strategy, but I want to show you something.
40:35
And then I would put up the 10 worst drawdowns going back to, in some cases the 1920s. And instantly you knew.
40:45
If their reaction was, "Oh, fuck" you knew that that strategy was not going to be right for them. Dwarkesh Patel: Yeah.
40:53
Jim O'Shaughnessy: It was like, "I can deal with it. I can deal with it.
40:56
That I don't know that I'm going to be able to deal with that 65% drawdown in six months." Dwarkesh Patel: Yeah.
41:03
Jim O'Shaughnessy: But by giving, I believe that giving information ahead of time also helps you presort. Right?
41:12
And so I kind of do the same thing when I'm asking founders the questions as you point out about Marc.
41:19
That's a great question to ask. Why?
41:23
Because man, if you got somebody who cannot give you an answer to that, run away.
41:28
Hold onto your wallet, don't give him or her any of your money because they haven't thought it through. Now, I was super lucky.
41:38
I've been lucky all my life, and luck plays a big park, but I was the youngest, I was the martini baby in my family. Thank you martinis.
41:48
So the next person in my family is seven years older than I.
41:48
And my, I didn't know all, but one of my grandparents.
42:00
And my grandfather, who was incredibly successful in the oil business, ended up giving away 95% of his own fortune during his lifetime.
42:10
But wonderful guy, and he was lonely and he came, we lived in the same town.
42:16
And so he came over for dinner twice a week and I learned so much from him.
42:22
And one of the first things that I learned was what he called premeditating.
42:27
And what he meant by it is what we're talking about right now.
42:30
I'm a huge believer in the process of get an idea, write.
42:36
If you cannot write out your idea, it's a bad idea.
42:40
You haven't graft it yet, or it was a little flight of fancy.
42:47
But then if you can write it out cogently and it makes sense then what my grandfather suggested doing, and which I do with everything I do, this idea of premeditating, which is here's all of the ways this could go right.
43:04
And then there's another line when it goes right, will it affect me positively or negatively?
43:10
Here's all the ways it can go wrong.
43:13
When it goes wrong, can it affect me positively or negatively?
43:18
And by doing this kind of premeditation, it naturally leads to questions that you would not have thought of ahead of time.
43:28
Believe me, having done this for more than 40 years, it's almost magical, and I hate using that word, but it's true because it unlocks all of these parts of you that gives you a much better idea about A, how to steelman.
43:46
But also to have a good answer to your question. Dwarkesh Patel: Yes. Yeah.
43:52
It's funny because there's some cases where maybe you probably don't want to do something like this, or maybe you do, but if you think about you're getting married, maybe you, should you write down what are all the ways this might go wrong.
44:02
Jim O'Shaughnessy: I did it. I did do it.
44:05
Dwarkesh Patel: Oh, you did? Okay. That's funny. That's funny.
44:10
Jim O'Shaughnessy: I've been married knock wood, I've been married 40 years to the same woman, so. Dwarkesh Patel: Okay.
44:14
So maybe you should do that then I guess.
44:16
Jim O'Shaughnessy: It helps.
44:19
Dwarkesh Patel: But yeah, because writing is really interesting because what it does is you get to see all of the connections between your premises that you might have missed when you were just sort of had it all in your head and you didn't realize, "Actually two doesn't lead to three. Why did I think it did?"
44:38
You just didn't put it down in writing.
44:41
But often people get stuck in this sort of rut in their life where they have some story about, "I need to be at this job that I hate for the next two years so I can advance in my career." Are you sure? Think about it.
44:55
Is there really no other way you could do this?
44:56
Write it down, write down your entire plan.
44:58
And it's just usually they find out that this might be a way to just reinforce the status quo bias.
45:04
If you don't really want to go out interviewing, you don't really want to think about what you might be doing with your time and you can just get stuck in this rut and come up with some sort of story about why this is the optimal thing for you to be doing.
45:13
If you just haven't thought about it that hard, if you haven't written it down.
45:17
And it's really helpful to kind of just get your decision-making on paper when you're coming up with these sorts of life changing or a large asset changing decisions.
45:28
Jim O'Shaughnessy: Totally.
45:30
And that's been one of my guiding principles.
45:34
People, just because you were born with your human OS at the factory settings doesn't mean you got to leave them there.
45:44
And one of the things that I have found through researching this is especially the works of Will Storr, we are to be charitable, unreliable narrators who are confabulating stories, rewriting memories and doing so without really consciously being aware that that's what we're doing.
46:09
And that's how you fall into confirmation bias to speak to what you mentioned, this is what's going to be best for me.
46:17
When you do that and try to convince yourself of that, you turn your thinker off.
46:22
I wrote a big thread on Twitter about how to reprogram yourself.
46:27
The thinker can think anything it wants. Right?
46:30
It can think that the world is a wonderful place and that the universe is helpful or that the world is a dark and horrible place and that the universe is out to get me.
46:42
And what happens is once your thinker stops thinking, it throws it over to the prover.
46:49
And guess what your prover does?
46:51
Your prover proves what you believe.
46:54
And when you, obviously this is a very simplified version, a fellow by the name of Dr Ore came up with, but it's very helpful.
47:03
Like George Box, all models are wrong, some are useful.
47:08
And so one of the things that I find is by not trying to look for all the good reasons, what you're doing there is you're confirmation biasing the entire situation.
47:24
You're skewing it to a point where you are actively limiting and prohibiting information that would contradict what all of these great reasons, you literally go blind to it. You don't see it.
47:41
And so part of the exercise, as you rightly point out is it opens up the mind to start thinking, "Oh, okay, so maybe I hadn't thought of that."
47:53
And then it's pulling on a thread. Right?
47:57
And the benefits of premeditating I think are numerous and incredibly useful.
48:08
And but also the idea, how are you going to react to failure?
48:14
Why does the fear of failure stop so many bright people from following what they want to do?
48:21
And this is going to be a nice segue into our talk about genius and innovation.
48:26
A lot of people really don't understand that if you really could just look inside someone's mind, they're not thinking about you, they're thinking about them.
48:40
And so one of the outer orientation I think is a horrible part of human OS.
48:47
It's really good for learning cooperation, for learning to build networks that can create brilliant things.
48:55
I'm a huge believer and fan of loose networks.
48:58
And I think that we now finally have the technology and tools to put together some of the coolest loose networks in history.
49:06
But what you want to make sure of is the fact that failure far from being something to be embarrassed about, it is one of the greatest opportunities to learn more than you've ever learned about any subject.
49:24
And if you, let me put it this way, my former job, we managed assets normally for quite successful people. Right?
49:35
I can count on two hands and I don't need all the fingers and the thumb on this hand, for the people whose objective was, "I want to be rich."
49:47
When you talk to these people, their objectives are, "I wanted to find a new energy source.
49:55
I wanted to figure out this aspect of computing. I need..."
50:01
And we're going to get into Unix and Linux in a minute here, but "I need this right now." Right?
50:07
And so it was almost never, "Oh, I want to be rich."
50:13
It was, "No, I'm obsessed about this particular problem. I want to solve it."
50:20
And also an openness to, you think of Edison, right?
50:25
I've only discovered a thousand ways not to make an electric light bulb.
50:31
That's information via negativita. Right?
50:34
And it also starts honing you towards the, "Okay, tried failed, tried failed."
50:39
Like Beckett's try again, fail again. Try better, fail better.
50:46
And so it's an iterative process that I've found.
50:50
But that, it leads me to, one of the things I love about your work is you really think deeply and come up with different ways of looking at things.
51:00
And when I was reading your stuff, I'm a huge Thomas Kuhn fan, so you had me there almost like at hello.
51:08
But when you're talking about genius and innovation, I found myself saying, "Yep, yep, yep."
51:17
First off, cities, why are cities really important and part of the creation of genius?
51:26
Hubs, to get them down to a lesser level, right?
51:29
Like coffee houses in London, as the stock exchange was being formed. Right?
51:37
Those became the hubs of the people who were really, really interested.
51:40
And then networks, take us through, if you would.
51:45
Actually, I'm going to shut up.
51:47
Take us through your story, ‘The Mystery of the Miracle Year’, because you actually hit many of the answers to the questions I've just asked you, if you take us through that. Dwarkesh Patel: Yeah.
52:02
This is something that I noticed, when you read the biographies of a lot of great scientists, what you'd notice is they tend to have one or two years.
52:13
And we should come up with field defining discoveries.
52:17
And not just one such field defining discovery, sometimes two, three, four, five years ago on the list, some of the most important center discoveries in an entire century happened by one person in one year.
52:28
And that's really mysterious.
52:30
That's kind of a coincidence.
52:31
You would think, well, why this one particular year?
52:34
Are they having an entire field's worth of discoveries?
52:38
And you go down the list. So there's Einstein.
52:40
In, I think it was 1905 when he was just 25 he does special relativity.
52:47
He has four independent discoveries that really redefined how we think about what is light, the effect of why or why do particles bounce around and what is a constant there, so.
53:05
And you there's Newton, he has one such year when he's 21 or 22, where he not only revolutionizes optics, he comes up with the beginnings of the theory of gravity, kind of invents calculus.
53:17
And so this is really interesting, but you notice it doesn't just happen with scientists.
53:22
I don't know if you're familiar with the fantasy author, Brandon Sanderson.
53:26
He recently announced that during the pandemic, he has been writing a new collection of books separate from the ones that he was already writing.
53:37
And so he said he wrote five books in the year or two after the pandemic happened.
53:42
And so you think, okay, well, why do these luminaries tend to have these incredibly concentrated periods of productivity?
53:48
And you go ahead and you can think, okay, there's a few possibilities here.
53:53
One is that maybe there's just a brief amount of time in your life where you're young and you have the intelligence and the fluidity of youth where you can just kind of think through problems really fast.
54:07
There's this famous stuff about how mathematicians. Jim O'Shaughnessy: Yeah.
54:10
Dwarkesh Patel: After you're 30 or 40, you might as well.
54:12
Dwarkesh Patel: Mathematicians, after you're like 30 or 40, you might as well, you go out to pasture or something.
54:15
So maybe you have to be really young to have that sort of intelligence.
54:18
But then you also need to be old enough to have awareness of what's happened in your field and understand all the relevant topics.
54:26
And the coincidence of those two intelligences is maybe only a year or two long in your life there.
54:32
Another possibility might be that if you do become successful, if you win a Nobel Prize, you're never going to have free time again.
54:40
You're going to be on all these committees, you're going to be the head of your department and you are never going to get the chance, do the deep work that leads to all these great insights.
54:49
And there are these famous sad stories about great scientists.
54:53
If you think of somebody like John von Neumann, he was probably one of the smartest people who ever lived, if you've heard, even if half the stories about him are true, he was by far the biggest genius ever.
55:05
But if you look back on his career, he obviously had a lot of important discoveries, but there's nothing field defining that he ever did.
55:14
And you can think about why that is.
55:16
And you look at his career and he was involved in coming up with the implosion device for the Manhattan Project bomb.
55:26
And so he was recruited by the government to do that.
55:27
After the war, he's recruited by the government to do a whole bunch of stuff about making sure the Soviet Union were on part of the Soviet Union in terms of computing and other things.
55:37
So because he was a genius, he just never had the free time to just independently do discoveries.
55:41
He was always recruited for some important project.
55:43
And I'm not saying that we shouldn't have had him help us defeat the Nazis.
55:46
That actually does seem like a good use of his time.
55:48
But maybe he should have also had some time to be able to frolic in the landscape of ideas.
55:53
But generally just a really interesting question.
55:59
Why is a miracle year a thing?
56:00
I still don't feel like I have a good answer to it.
56:03
Jim O'Shaughnessy: And I think it also is discipline dependent.
56:09
I think I can give you all sorts of counter examples for literary people who started, like painters who started late or came into their own late in life.
56:24
And so I think that there's more fluidity there than we might at first suspect.
56:33
And then there's also the Matt Ridley notion where he says, listen man, if Edison was run over by a car the moment before he figured out that the correct way to do the light bulb, it might be delayed, but someone else is thinking about it too.
56:52
And you used Newton as your example, well, Leibniz had quite a fit with Isaac Newton because Leibniz and Newton independently invented calculus pretty much at the same time.
57:09
And finally, the quantum guys especially, a lot of these formulas started percolating, so to speak, in many minds in many of these brilliant minds at fairly contiguous times.
57:28
And so it was maybe just that Heisenberg got it on paper faster or Einstein used better imagery.
57:39
I remember one of Einstein's things when he was talking about E equals MC squared and relativity, when he was talking to laypeople he would say, I had a dream that I was riding on a beam of light.
57:56
And so Einstein had this ability to put it in a colorful, memorable way that perhaps an equally competent researcher in physics wouldn't have that ability.
58:13
He was tongue-tied or she was tongue-tied.
58:17
So what do you think about Ridley's idea that in some senses it can extend to this idea that maybe some of these innovations were already baked in?
58:32
Dwarkesh Patel: That's a really interesting point.
58:35
I actually really enjoyed his book and he was in Austin for a live event while I was there as well.
58:41
And I actually asked him about this and what I asked him was, at the time I was studying computer science in college and I said, listen, I might start a startup, but if you're right, then that startup is going to be invented anyways by somebody else. So why bother?
58:57
What is the use of this if somebody else is going to do the innovation anyways?
59:02
Why should anybody, individually feel compelled to innovate, which is your entire thesis that we should really value innovation, if it's going to happen anyways?
59:12
I don't remember if he had a good answer to that.
59:14
I do remember part of the answer was like, don't you want to be the one who makes all the money?
59:21
But there's some cases where I think it's absolutely true that, I think it probably with special relativity, it was on the tip of the tongues of so many people.
59:32
With generality, I feel like it was a different story- Jim O'Shaughnessy: I agree. Dwarkesh Patel: ...
59:35
Where Albert Einstein it took, I don't know, five, 10 years of deep thinking and I don't know if anybody was on his heel.
59:39
So I don't think we would never have discovered it, but it would've been a longer delay.
59:42
And when you're thinking of something like a fundamental advance like that, how much does it cost the world to be 10 years behind in physics?
59:49
I don't think that's a negligible cost, but there are many cases where the pieces are there for years, decades sometimes, and somebody doesn't come along to fill in the line so to speak, until quite a bit later.
1:00:03
I think Bitcoin is a case of this actually, where if you think of the cryptographic tool that enabled that technology.
1:00:09
They were around for many years before somebody actually put them together in this distributive ledger idea.
1:00:14
So we shouldn't take for granted that these ideas will just come about.
1:00:20
I think that's often the case, but not always.
1:00:23
Jim O'Shaughnessy: I agree with that assessment and it leads me to Alea Iacta Est.
1:00:33
I think that is the Latin for The Die Is Cast, and that is reportedly what Caesar said when he crossed the Rubicon, which was the border between Rome and outside Rome.
1:00:47
No Roman general had ever brought armed men across the Rubicon.
1:00:58
And so I think it's a classic example.
1:01:03
I was fascinated by this by the way, every culture has a burn the ship's myth.
1:01:11
And so we might hear it here about the conquistadors and how they burned the ships. No.
1:01:18
I went on a hunt and I found these stories exist in every single- Dwarkesh Patel: Wow. Jim O'Shaughnessy: ... Culture.
1:01:25
And so it is the die being cast.
1:01:30
What that infers and implies is that same as the burn the ships, the ships are gone that way is now closed to us.
1:01:41
Even if we want to go back, we can't go back.
1:01:44
Die is cast, I'm across the Rubicon with armed men.
1:01:50
I can't tiptoe back across the Rubicon.
1:01:54
And so it's this idea of existential risks at the highest levels of play are made with this, the Latin for decide is decernere which means to cut off.
1:02:13
And so this informs the answer to your question, I think.
1:02:19
I believe because you want to make the money, no offense to him, maybe he said that maybe he didn't, I think that's not the right answer.
1:02:28
I think that people are designed, and I don't know what percentage of this is genetic structure.
1:02:36
I don't know what percentage of it is those genes getting switched on by your environment in which you grow up.
1:02:43
But I do believe that when I look at the creators, the innovators, and by the way, this is applicable across industries and domains.
1:02:56
So I find this in scientists, I find this in mathematicians, I find this in oil artists, in poets, in all sorts of people.
1:03:07
Quite frankly they're obsessed and their obsession is driven by an insatiable curiosity.
1:03:17
So I think that the broader answer there is leads into one of your ideas, which is because you've said that we get the 20s all wrong, instead of locking kids in these dead end jobs to make rent and party on the weekend and all of those sort of normal paths, what
1:03:46
we ought to be doing is hunting kind of what we're doing at O’Shaughnessy Ventures with our fellowships and with all of that, one should be hunting for people who need to be given the time to really get deep into a subject to really think about it. So let's go into that right now since we're talking about it, so make the case around
1:04:11
So let's go into that right now since we're talking about it, so make the case around that statement that you think, sadly, we ought to invert your standard PhD program and do it the other way.
1:04:30
Dwarkesh Patel: Well if you look back at the history of science, a lot of the great ideas do come from people.
1:04:37
We talked to Einstein and Newton, they were in the early twenties.
1:04:41
I don't know why this is the case.
1:04:43
It could be that maybe that's when you're at your peak of intelligence.
1:04:46
Maybe that's when you haven't absorbed enough to have the ideas of your field that, we were just talking about Kuhn earlier, any sort of new paradigm you would come up with is fizzled out because you are just inebriated in the existing paradigms.
1:05:06
But I think back, not even scientists, I think back on my own journey where I graduated college and then I was probably going to become a programmer at big tech X, and instead, somebody who listened to the podcast at a time really liked it and they gave me a $10,000 grant about a year ago, and that was enough for me to really jump in and try to make something of this project and it ended up growing.
1:05:34
But something that's normal that early, I'm obviously no scientist or anything, but what if you're working on something new and that's why I really admire what you guys are doing at O’Shaughnessy Ventures can really help people kickstart something interesting projects, interesting ideas.
1:05:49
As for scientists, I do wonder, so there's an argument you could make where listen, the reason they could do it all this great science in their early 20s back in the day was because there just wasn't that much you needed to learn before we got the cutting edge.
1:06:01
Whereas today, you probably need to be in your 30s or 40s by the time you've absorbed enough of the information to be at the forefront.
1:06:09
That might be true, but even if it is the case, I do think it's probably there should be some, we shouldn't just put all our chips into that bet that we're sure you need to be in your 30s and 40s if we're going to make foreign discoveries.
1:06:26
We should at least let a few of our young people have the opportunity to really just jump heads first into a field.
1:06:31
I actually have a funny story about this.
1:06:33
I don't know if you're familiar with the computer scientist, Scott Aaronson? Jim O'Shaughnessy: No.
1:06:38
Dwarkesh Patel: He's like the top quantum computing theorist in the entire world, he's actually now working on AI by the way.
1:06:46
He's got hired by Open AI to work on AI safety.
1:06:50
But anyways, he was my professor in college and he was telling us about this algorithm for proving the upper bounds of the complexity of certain algorithms.
1:06:59
And so this is an incredibly important result in the field of computation, one of the foundational results.
1:07:06
And he says, you know I actually almost proved this result of myself in 1999, but somebody beat me to the pond in just a few months earlier.
1:07:13
And he said, I was so disappointed at the time and I thought, wait, how old was Scott Aaronson have been in 1999. He would've been 19.
1:07:25
So there are some people that are like that out there who are just prodigies and you want to get them at the edge of their field at the frontier as fast as possible.
1:07:35
Jim O'Shaughnessy: Absolutely agree.
1:07:37
And wouldn't be doing the fellowships if I didn't think that was very, very important because distractions, life does in fact get in the way, especially if you have a significant other and or children and or parents that you need to care for. There are so many.
1:07:59
And then not to mention the distractions of dooms scrolling on Twitter or watching TikTok for four hours.
1:08:10
If you have the ability to really think deeply and work deeply, because I also think one needs to work on it as well.
1:08:20
Doing is thinking, I think, and by that I mean by doing, you have the errors pointed out considerably faster than if you are just doing it in your head.
1:08:35
I include writing it out as doing.
1:08:41
And so I think that that is a very valid way of looking at this.
1:08:50
You also point out that you think that there are intellectual market makers.
1:08:56
Dwarkesh Patel: Actually, before we go to that, I think another point what you said just raised about this subject is I'm really optimistic about the ability of AI to help reduce the load of memorization we need to foist on people to go to the edge of their careers.
1:09:16
People have seen this with Chat GPT obviously you can just ask something, it'll tell you the existing knowledge so that you can just move on from beyond that.
1:09:24
But I actually built something myself, a tool.
1:09:28
I don't know if you saw this on Twitter or anywhere else.
1:09:31
Jim O'Shaughnessy: No, actually it was going to be one of my questions because I'm fascinated about it.
1:09:34
Dwarkesh Patel: But I call it Google Books on steroids, so- Jim O'Shaughnessy: That's awesome. I love that.
1:09:39
Dwarkesh Patel: But it basically pulls up the most relevant passages to any sort of search query you could put.
1:09:47
We index thousands and thousands of books, history, economics, popular science textbooks, and you ask the question, why did Rome fall? What is the tracheotomy?
1:09:57
What is the sequel database?
1:09:58
Just think of any question you can think of from the classics to the newest textbook, it'll pull up the most relevant passages from all these books so that you can find this information out there and you don't have to memorize all this stuff.
1:10:11
The information, this semantic search ability that AI has, and not only that, but question answering on top of that where the AI gives you a natural language response based on this information that it finds I think is really going to change, not this tool maybe in particular, but just generally this ability of how science is done, of how people get information are able to synthesize it together to make new discoveries.
1:10:33
Jim O'Shaughnessy: Totally. 100% agree.
1:10:37
I am very bullish on if we get it right, I think that AI is the third technological revolution and I think it will fundamentally impact us as a species.
1:10:57
And I know from reading you agree.
1:10:59
And you also make the point that if it's not AI, it's going to be something like gene splicing with CRISPR.
1:11:07
We are at a fundamental inflection point in my opinion, and I think it's cool as hell. Are there dangers?
1:11:17
Of course there are dangers.
1:11:19
There are dangers in everything one does and so I'm not in the least bit pollyannish about any of this. I'm not going to be Dr.
1:11:27
Pangloss and say that we are living in the best of all possible worlds.
1:11:33
I do think however, that with this combination, both of AI, but also with having the largest variance amplifier in history, my friend Matt Clifford.
1:11:45
Clifford calls the internet that, and that also gives the ability to build loose networks by interest.
1:11:58
Those were really hard to build in a pre-digital era.
1:12:03
If you were in Georgia, the state or Georgia the country, and you were interested in Lionel railroads just to pick something at random, there was no way you could ever communicate with one another.
1:12:17
You couldn't find that fine fellow down there in Georgia and this guy would simply say, cannot find. Now you can find them.
1:12:29
And so these loose organizations with the addition of what you just mentioned, the ability to not have to memorize, that is such a key point and I'm glad to hear you make it because when I was younger, memorization, if you could memorize things, which I people thought you were smart, basically it was like, oh, he's smart.
1:12:52
He knows 1066 is the battle of Hastings and he even knows who won.
1:13:00
That's meaningless for the most part.
1:13:03
It's interesting in isolation, what I think true innovative thinking is synthesis.
1:13:12
And if you can now using your Google books on steroids, which I will use, things like that.
1:13:23
But now we have the ability to have all of that there.
1:13:27
And I even think that if we get the AI right, we're going to be able to look into places like liminal spaces that were until now blocked to humans because we just didn't have the bandwidth to be able to go into those spaces.
1:13:47
So I definitely think that you're right in terms of where these things can go.
1:13:53
And I think it's right by the way to think about the downside because AI is an omnidirectional technology.
1:14:04
It can impact a ton of things and learning being one of them, one of the things that I'm very interested in learning at all levels, but I'm particularly interested in teaching younger kids because I think we do a crap job of it today, at least in this country.
1:14:26
And I think that it's antiquated and it's been allowed to persist from the days when frankly they were trying to get people who could do the same thing over and over and over again and not think too much.
1:14:44
So the Pink Floyd saw it a long time ago when they were, teacher leave that kid alone.
1:14:53
So I think by the way, that might be another part of the youth question and coming up with great things.
1:15:01
Unfortunately, I think that the system, at least here in the States and in Western Europe, crushes creativity and tries to make people fit in because they're thinking top-down methods about how do we make you a useful citizen?
1:15:24
And in AI lingo it is, let's maximize the objective function for GDP.
1:15:35
And when you do that, you get all sorts of secondary and tertiary effects that you weren't necessarily thinking about when you were trying to maximize the objective function.
1:15:45
So I think that getting back to geniuses and intellectual market makers, I'm fascinated by that idea by the way.
1:15:56
Do you think that curation is the same thing as an intellectual market maker?
1:16:03
Dwarkesh Patel: Sorry to interrupt that question again, we will get to it, but I actually thought what you said about kids was really interesting and in fact, I don't even think that the system is necessarily optimizing for GDP.
1:16:16
I think it's just an unconscious set of procedures that's built up over the decades.
1:16:22
But if you're really trying to optimize for GDP, as you said, we need creative people to come up with new ideas for economic growth.
1:16:28
Jim O'Shaughnessy: Exactly.
1:16:29
Dwarkesh Patel: So to play, we were talking earlier about steelmanning the opposite idea.
1:16:34
And so here's how my steelman up the opposite idea.
1:16:36
There's this really interesting review of a book that Matt Lakeman wrote the review of this book and the book is ‘Little Soldiers’ and it's written by this woman who is of Chinese descent but grew up in America and she has to live in China for a few years.
1:16:56
And therefore her child who's like five or six years old, he goes to Chinese schools during this time.
1:17:04
And she notices basically that these teachers, even in these really upper class schools, are basically abusing the children.
1:17:12
They're forced to draw raindrops for hours on end.
1:17:15
Her kid hates eggs and the teachers force-feed him eggs so that he can get over it.
1:17:21
It just almost sounds really abusive.
1:17:24
But then she notices actually my kid, when I take him back to America with his cousins, he's way more disciplined. He seems more mature.
1:17:32
He's ahead in his studies now.
1:17:37
And so I thought that was an interesting different perspective on the idea of having, I'm a huge proponent of giving kids freedom, but there is this thing we know how American adults will complain about, I'm bad at adulting, and I wonder, there's a story to be told about maybe your teacher just needed to force you to keep drawing raindrops for hours on end until you're bored out your mind.
1:17:58
So you can learn how to do that.
1:18:02
But that's not really my perspective.
1:18:05
My perspective is that we should give children orders of more magnitude rights and responsibilities than they have now.
1:18:11
If you read the biographies of these people who grew up a century ago or 50 years ago, and I'm curious if this is your experience, but you read of somebody like Malcolm X's biography.
1:18:22
He's traveling around cities when he is 14, meeting interesting people coming up with his own projects, doing things on his own.
1:18:28
And I think that really breeds a level of independence and curiosity and adulthood and maturity that we deprive kids of by putting them in this prison for eight hours a day.
1:18:38
Jim O'Shaughnessy: I agree with that.
1:18:41
And I think we're making an investment in synthesis school, which is kind of Ad Astra 2. 0.
1:18:50
And what they're trying to do is teach kids how to think, not what to think. And it's aptly named.
1:18:59
Because a synthesis of these subjects and ideas where the kids can follow their own curiosity.
1:19:09
It's not like a free for all.
1:19:11
They have them working on specific problems.
1:19:14
But what's interesting is the child learns that there is more than one way to solve a problem, but they also learn that there might be an optimal way to solve a problem.
1:19:28
So being able to have that kind of freedom I think is very important, especially for young people in learning because it also builds, I think learning should be fun if I'm a big fan of Africa, and if you go there, especially the predators and watch them, they spend 80% of their time either sleeping or playing.
1:19:55
And playing if you watch closely is lesson learning.
1:20:03
The lion cubs who are practicing taking each other down.
1:20:08
Obviously that's going to be important to them when they're hunters in the future.
1:20:13
But I think that the idea of linking fun, linking open-ended without the correct answer machine being installed in your mind is all to the good.
1:20:31
But again, I want to get back to intellectual market makers.
1:20:34
You're good at that, by the way. You're really good.
1:20:37
I have a guy who works for me, he goes, you know what I love about you, Jim?
1:20:42
Is that the real fun is in the digressions.
1:20:45
And he goes, but you always do get back to the same question.
1:20:50
I'm trying to maintain that discipline here.
1:20:53
Intellectual market makers.
1:20:56
Is that the same as curation, do you think? Dwarkesh Patel: Yes.
1:21:02
That's an interesting question.
1:21:05
Maybe these are just terms for the same exact kind of thing, but I do think whatever they're referring to is very valuable.
1:21:12
You'll often hear people dismiss people.
1:21:14
I think we actually saw this with what happened with Lex, actually, if you were paying attention to the whole Twitter drama.
1:21:19
But we often dismiss people who provide people with ideas that are already out there, but curate them and synthesize them together in a format, in a medium, in a language that the audience can understand.
1:21:34
And we say, oh, well, you're just expressing an idea that's already out there.
1:21:37
You didn't come up with something original, but that's actually a valuable service.
1:21:42
If you have an idea and nobody's heard about it, that's no good.
1:21:46
And you need the people who are popularizing these ideas.
1:21:49
They provide actually a similar service to what market makers provide in the actual financial marketplace.
1:21:56
And without market makers, like markets wouldn't exist almost a definition.
1:22:01
But to be able to almost buy this idea that sends some dusty library that nobody has ever opened since like 1960, and give that to people over a Twitter, over podcast or a blog post, that's a valuable service.
1:22:16
And I think you were talking earlier about how as Chairman of Stability, that's one of your responsibilities of expanding on these ideas and providing them to the public so that there can be these broad discussions about these new technologies.
1:22:29
I think that's immensely valuable.
1:22:30
You can't expect people to be able to talk in terms of the details of the transformer.
1:22:36
You need to be able to engage people in this broader conversation.
1:22:40
And if you think of these people, think of something like Malcolm Gladwell, if you've read his books, he's basically making money or not making money.
1:22:52
This career is basically profiting off the spread from this obscure study about hockey players and their birthdays or something and his book ‘Outliers’ and the spread between that and a New York Times bestselling book. But good on him.
1:23:07
He popularized the study.
1:23:09
Jim O'Shaughnessy: I agree.
1:23:12
I've read all of his books.
1:23:14
I don't like them all, but I think you're right.
1:23:19
I think he provides a very useful service.
1:23:23
And Bill Bryson is another guy that I think of.
1:23:27
I loved his book ‘America One Summer 1927’, because if you read history, I'm a big history fan, so I kind of remembered all of this stuff.
1:23:40
But he's such a good storyteller and the way he synthesizes the way these things connect to one another.
1:23:49
I loved reading that book. It was fun.
1:23:52
It reminded me of all the stuff that I kind of remember reading about in a much drier format.
1:24:01
And so one of the things, and the reason I asked you about curation versus intellectual market makers is like information is abundant. Attention is scarce.
1:24:14
And so I'm thinking less of the genius who might be inventing the next hyperdrive and I'm thinking, more of the person who simply wants to keep up with what's current and what are the new ideas and what are the challenges and the opportunities, I guess, would be I think a very valuable thing to be able to provide to people.
1:24:42
And I think that it also crosses over with your intellectual market making.
1:24:50
You had another thing which I really do believe in, which is by doing things like these grants, by doing things that don't really have strings attached but give maximum freedom to the person who you think has something to offer, what you're doing is kind of getting a long-term call option on them. Dwarkesh Patel: Yeah.
1:25:12
Jim O'Shaughnessy: You want to talk about that for a minute? Dwarkesh Patel: Yeah.
1:25:16
This idea came about because I was thinking about, there's this interesting thought experiment where you can say, listen, imagine this kid in high school and this kid is the president of five clubs, he's on the varsity tennis team and he's an A student.
1:25:36
And now imagine another kid and she has started a business that is earning four figures monthly.
1:25:43
Now, which one sounds more impressive?
1:25:46
The kid who has maybe a web development business that's earning four figures or the one who has basically completed the existing tracks of National Honor Society, tennis varsity team and so on.
1:25:58
I would say that the kid who started her own business sounds more impressive. Now, why is that?
1:26:03
It's not necessarily the case that she's put in more effort, has put in more hours per week than the other kid.
1:26:10
What's interesting is the reason what she is doing sounds more impressive is because it's a fundamentally more novel thing.
1:26:19
It's harder to think about how does a kid in high school start a business that's earning four or five figures?
1:26:25
Where it's easy to think about, okay, I get how you become president of a National Honors Society.
1:26:29
That's like a pretty surf over thing.
1:26:30
And then you can expand on this and say, well, what generally is the thing that makes young people impressive?
1:26:39
When young people do something that a person older might have done, why is it more impressive that a young person has done it?
1:26:45
And then there's a really nice financial metaphor for thinking about this, which is just think about it in terms of how do you think about the value of an option?
1:26:54
To use the lingo, like the Black-Scholes formula, what makes the right to buy something valuable?
1:27:02
Well, you really want to maximize the upside.
1:27:06
That's the gist of what makes the option valuable.
1:27:10
And what is a thing that maximizes the upside?
1:27:12
Well, you want a long duration between now and the time the option can be exercised.
1:27:19
And if you think about young people as a sort of option - when you're investing in somebody's talent, you are kind of buying an option on them - the younger they are, in some sense, the bigger distance there is between their current date and their time to maturity when you get the full advantage of them as an employee or them as an investment, or them as just somebody who is in your network, somebody who's your protege. So that explains that.
1:27:44
How about why is the young kid who starts a business more impressive than the person who just does the existing track of hobbies?
1:27:52
And I think this is because another thing that makes an option valuable is if it's high volatility.
1:27:57
Because think about it, the more volatile it is, the greater the opportunity that the thing is going to just go to the moon.
1:28:04
You'd rather have an option on Bitcoin than one on IBM, so I think those two things combined explain a lot about why a young person doing something really impressive has a attractive pull and why it's right to invest in them in any way you can.
1:28:21
Jim O'Shaughnessy: Yeah, I think that I agree, and the point about volatility is not well understood in my opinion.
1:28:32
I have a good friend who's quite brilliant here in New York City, and when we get together, he often chides me, " Jim, will you please stop telling people to stop being deterministic thinkers?
1:28:44
Will you stop trying to tell them why probabilistic thought is far superior?"
1:28:49
And I'm like, "Syd, what's wrong with that?"
1:28:52
He goes, "You're either long ball or you're short ball."
1:28:59
He goes, "The vast majority of people are short ball.
1:29:02
They want to sell, they want insurance, they want certainty, they want low variance.
1:29:11
Whereas guys like us, we love volatility, we love uncertainty.
1:29:17
We're a much smaller part of the overall distribution."
1:29:22
And as I'm listening to him, I'm like, "You know, you are kind of making sense here," because if you think about it, if appetite for volatility were normally Bayesian distribution, there is no Jeff Bezos, there is no Elon Musk.
1:29:41
There is no person who is able to burn the ships, who is able to cast the dye.
1:29:53
And when I really thought about that, I thought, "I think he's right."
1:29:59
And the reason I'm thinking about that is the person who would be conventionally thought to be, "What a great kid.
1:30:08
Look, he's at the top of the Honors Society, he's on the top of the whatever."
1:30:16
And I don't mean in any way to dismiss those achievements.
1:30:19
I think that's great, that's great.
1:30:22
But they're walking up well worn paths and they're really not going to find anything new there, I don't think. Dwarkesh Patel: Yep.
1:30:31
Jim O'Shaughnessy: Whereas I too would think more highly of the woman who started the company in high school because that shit's hard.
1:30:46
And when you have one where you have a guide already to all, what do you have to say to be the one who gets into the club?
1:30:55
Again, I always test things against, is this consistent with evolution?
1:31:01
So it's kind of like, yeah. What's evolution?
1:31:05
First you've got to fit in because if you don't fit in, they'll exile you, and back then, the world killed you.
1:31:14
It was not a very friendly place.
1:31:16
And so fit in, yes, but then what do we want to do as humans? We want to stand out.
1:31:22
And so on the path of valedictorian, now, my mom was valedictorian, I'm very proud of her that she achieved that.
1:31:31
But the fact is you knew, the rule book was right there.
1:31:35
It was just like, to do this, you must do A, B, C, D, E, and F.
1:31:41
Whereas the woman who started her business, yeah, there are things you can read.
1:31:48
Yeah, you can listen to people who've done it in the past.
1:31:52
Yeah, you can learn from the mistakes of others, although as Doug Adams says, humans who are uniquely situated to learn from the mistakes of others are remarkable for their disinclination to do so.
1:32:06
Dwarkesh Patel: There's a quote from Will Durant that “a wise person can learn from the mistakes of others.
1:32:13
A fool cannot even learn from his own mistakes.
1:32:13
” Jim O'Shaughnessy: I love Will Durant.
1:32:18
I've read the entire- Dwarkesh Patel: Oh, really? I'm a fan, yeah. Jim O'Shaughnessy: Yeah. 13 volumes. Dwarkesh Patel: Really?
1:32:25
Jim O'Shaughnessy: I love the books he and Ariel did.
1:32:27
I love ‘The Lessons of History’. Dwarkesh Patel: Yep.
1:32:30
Jim O'Shaughnessy: Huge history nerd and history fan. Dwarkesh Patel: Yeah.
1:32:34
Did you read ‘Fallen Leaves’, his last collection? Oh yeah. It's so beautiful.
1:32:39
It's one of my favorite books.
1:32:41
Jim O'Shaughnessy: Well, it's almost poetry really. Dwarkesh Patel: Yeah.
1:32:45
Jim O'Shaughnessy: Prose.
1:32:47
So I've got to be mindful of time because there's another thing I want to cover, and maybe this is just recency bias on my part, but you actually interviewed Sam Bankman-Fried. Dwarkesh Patel: Yes.
1:33:02
Jim O'Shaughnessy: And effective altruism, and you also made a statement that I hadn't heard it put this way in the past and so it struck me, and you said, effective altruism essentially provides an effective outlet for the billionaires or centi-millionaires who would've been Caesar or Napoleon in the past.
1:33:30
What's interesting about that to me is my friend and we also invest in Entrepreneur First, his company, Matt Clifford made exactly that argument when I had him on Infinite Loops.
1:33:46
But was there anything about Bankman when you were talking with him, things that make you go, hmmm? Dwarkesh Patel: Yeah.
1:34:01
Well, one thing I really took away from our conversation is clearly, this guy is incredibly intelligent.
1:34:07
I tried hard to come up with questions that he had not heard before, I hadn't heard in any other interviews.
1:34:12
I tried to really dig into the business, dig into his philosophy, and I tried to ask unique questions about that.
1:34:18
And the way he responded to them, the speed at which he responded, the composition of those answers, the way he responded was like, "Oh, I was just talking with somebody about this.
1:34:30
Let me just give you this paragraph essay long response of this perfectly put together list of points."
1:34:35
And so he's incredibly intelligent, that's one thing I took away.
1:34:40
I think in retrospect, I probably should have asked a little more about Alameda, probably should have asked a little more about that liquidation policy.
1:34:49
Was there anything interesting about the...
1:34:51
I think a lot of these things are things where in retrospect, you can think back on and say, "Oh, this is kind of a tell."
1:34:59
But if the business was running fine, I would've never suspected that that particular thing I saw or heard was a tell.
1:35:05
So for example, one of the things his comms people said is I'm not allowed to ask about Alameda, and initially, that sounds suspicious but I've had other guests come on who are business people who have like, "Listen, this is the thing.
1:35:18
I'm on the board of this thing so I'm not allowed to talk about it."
1:35:20
And so I'm not immediately suspicious that they're necessarily a fraud because of that, so it's hard to say in advance whether...
1:35:28
There's a lot of hindsight bias there, you know what I mean?
1:35:31
Jim O'Shaughnessy: I do, and I'm actually delighted to hear that answer because it shows that you are very aware of everything's obvious retrospectively. Dwarkesh Patel: Right.
1:35:44
Jim O'Shaughnessy: It's like, well, of course, and people don't even realize they're doing it.
1:35:52
So I think of the global financial crisis of '08.
1:35:57
The number of really smart people who I know had no idea what was going to happen, fervently believe, and now you've got to get into Will Storr and the fact that we are confabulating our own memories and everything to make ourselves the hero of our story, but they actually and passionately believe they knew that this was going to [inaudible]. No, you did not.
1:36:32
It's gotten to the point where I actually keep a list of any kind of pattern recognition I see or think I'm seeing because I've got to keep myself honest.
1:36:44
Because one of the things that I've learned is that our brain conveniently does a memory dump down the memory hole of all the times that we were wrong, and it continually reminds us, "Jim, you were so right. You were so right."
1:36:59
And it's a process that many aren't even aware of, and so I love the fact that that was your answer.
1:37:07
Let's talk a little more broadly about effective altruism.
1:37:12
I must confess that my grifter meter went off as I listened to many people [inaudible] effective altruism.
1:37:29
So what did Hemingway say?
1:37:31
To be a great writer, you need a rock solid gold plated bullshit detector, and I was kind of a detecting a lot of bullshit.
1:37:41
Tell me why I'm [inaudible]. Dwarkesh Patel: Yeah.
1:37:44
I think there are certain things that maybe should give off that vibe.
1:37:51
This is one of those things where the crux of it clearly seems like a good idea, that people want to give to charities so just think carefully about which charities are best and which ones will have the greatest impact per dollar given.
1:38:05
That seems like a straightforward and hard to argue with idea, then you should donate more money to these charities.
1:38:12
Then I think a problem these things often have is that when the movement is really comprised of these elite people who come from these intellectual backgrounds, is you need to come up with newer and newer ideas that are weirder and weirder.
1:38:27
You need to be more and more contrarian.
1:38:29
And so sometimes, you can get into this spiral where I'm sure you saw this stuff about how they calculated that animals in the wild suffer a lot, and therefore, maybe that's not a good thing.
1:38:42
Maybe having wilderness is actually increasing the amount of suffering in the world.
1:38:45
I'm not saying most effective altruists would endorse that but that is a sort of trend that can happen.
1:38:51
And another thing that could happen is...
1:38:53
Just generally, the people throughout history, the leaders who have been the men of ideas don't necessarily have a great track record.
1:38:59
I'm not saying all of them are but if you think of Stalin, I think had a library of 50,000 books.
1:39:05
Jim O'Shaughnessy: He did. Dwarkesh Patel: Yeah. Yeah.
1:39:09
Just a lot of world leaders who we look back on as terrible people, they were intellectual people of ideas.
1:39:14
This is not to say that if your president is a reader, then he's going to sort of genocide or anything, but yeah, I am very sympathetic to the basic idea of the movement.
1:39:29
I do think that maybe no good thing can last, especially if you have this idea that we're going to listen to the community and you're going to improve, and there's weird dynamics that come from listening to the community where how do you get ahead in that sort of dynamic as you come up with these really weird ideas?
1:39:43
But I'm curious, why are you skeptical of it?
1:39:47
Jim O'Shaughnessy: I'm skeptical because I think I have a pretty good handle on human OS, and I have always been suspicious of virtue signalers because the data on what they actually do is very different from often what they say.
1:40:12
My friend, Rob Henderson, who's getting his PhD at Cambridge in psychology dubbed this luxury beliefs, and that's a good handle to put on it.
1:40:28
And I always am bothered by people who go out of their way to demonstrate how virtuous they are, because me thinks thou doth protests too much.
1:40:48
And so I am more taken by the people who do rather than talk about what they're going to do or whatnot.
1:41:04
So listen, I'm all in favor.
1:41:07
My time home horizon is infinite and it's infinite because I have grandchildren whose lives I want to be in a great world, and I love my children and I want to be able to pass assets onto both of them.
1:41:24
But there are also charities that I want to continue to persist in the world.
1:41:30
And so my time horizon luckily is infinite because hopefully, this will continue to compound and then we'll be able to fund some really cool things.
1:41:43
But I just look at myself and when we are talking about why I am doing what I'm doing, I'm not trying to fool anybody.
1:41:50
I'm doing this because I am interested in it.
1:41:54
I'm doing it for myself, to be just blunt about it.
1:41:59
And a lot of other people have been trying to say, "Oh, that's not true, Jim.
1:42:05
You're one of the biggest humanitarians I've ever known in my life."
1:42:09
And it's very nice and it's very kind of them to say that to me but I think it's fundamentally dishonest, and I think that effective altruism is a dodge in many respects.
1:42:25
"I'm not wanting to become a billionaire because I'm greedy and because I want to buy a palace in The Bahamas and I want to have orgies on the penthouse level of that particular property I'm buying. No, no, no, no, no.
1:42:42
I'm only becoming rich so that I can fund these wonderful things that are going to be so good for us in our future."
1:42:50
See, again, I cringe when I hear that.
1:42:54
I just get a sense of fundamental dishonesty. Dwarkesh Patel: Yeah. You know what's funny?
1:43:01
He had this thing about how, "I drive a Corolla so I'm one of you, I'm somebody who happens to have billions of dollars but I still drive a Corolla because I'm donating the rest of the money."
1:43:10
And I think this is a great trick because the thing is in the year 2022, it is impossible to buy a new car that is not amazing.
1:43:19
So just buy a car that's- Jim O'Shaughnessy: It could be a Kia, it doesn't matter.
1:43:25
They're all great, Dwarkesh Patel: Yeah.
1:43:28
But then you can just live in a $30 million house or something and then people will just have just one thing that an ordinary person would do and then that'll be the thing that comes up in all the articles.
1:43:37
But okay, so there's a way of looking at this where you say, listen, it may be virtue signaling.
1:43:42
It may be a way of people who have these grand ambitions of personal fame or wealth to signal that, "Hey, I'm still doing this for pro-social motivations."
1:43:51
But even if that's the case, if the end result is that they're giving away hundreds of millions of dollars or billions of dollars, while not committing fraud, then- Jim O'Shaughnessy: [inaudible] please. Dwarkesh Patel: Yes. Then that's fine.
1:44:05
I think in any society, there will exist people who have this burning desire to achieve for themselves and these people actually can often do a lot of great things.
1:44:16
And maybe they're dishonest about why they're doing the great things.
1:44:20
Maybe they build a valuable company and they say it's because they're doing it to help the world.
1:44:24
In fact, they also really want that personal fame and recognition.
1:44:30
But if the side effect is the things that they happen to do for the world, I can accept that people lie to themselves for things like that.
1:44:39
I lie to myself about certain things I'm sure, so- Jim O'Shaughnessy: Well, I think we all do, and that's why I prefer your alternate explanation, which is, well, Jesus, we've got to have an outlet for the Caesars and Napoleons in the world, because we're not going to let people distribute or cause horrible wars all across the various continents because they're ambitious.
1:45:06
So I think that's a better explanation of why this is reasonable.
1:45:14
I just think that, I try to be as honest with myself as I can be and I am doing a lot of the things that I'm doing because I want to do them.
1:45:30
That's honestly the answer, because I'm interested.
1:45:33
Why do you have an infinite films vertical?
1:45:36
Because I love movies and because I think Hollywood's been putting out shit for a long time.
1:45:42
They're not telling the inspirational stories, they're not doing the heroes' journeys.
1:45:47
And it's almost against their own economic interests.
1:45:50
If you look at the top 10 grossing movies of all time inflation adjusted, I think eight of them are classic heroes' journeys, and so I just believe that whenever...
1:46:06
My mom, who was great, I miss her dearly.
1:46:10
She had a saying which was, "The louder he spoke of his honor, the quicker we counted the spoons."
1:46:19
In other words, again, "I am so honorable. I am all these things. I am virtuous."
1:46:26
I think that's kind of bullshit.
1:46:30
And listen, do I know people who I think are quite virtuous and I think are incredibly honorable?
1:46:40
Of course I do, but they tend to be the ones who aren't banging on about it endlessly.
1:46:46
And so it just seems a bit like a grift or a con, and as you know, conman actually came from confidence man and it was one who made you feel confident in the scheme that he was trying to sell you.
1:47:08
And so, I don't know, I think you're right. I love the outcome.
1:47:12
My grandfather, super successful, he gave away all of his own money or 95% of his own money during his own lifetime.
1:47:22
But the message that I got was, "Money's a lot like manure. Jim.
1:47:27
If it's piled in one place, it stinks to high heaven.
1:47:30
If you spread it around, it's a great fertilizer."
1:47:34
And so I've always just thought of money as a technology really.
1:47:39
In and of itself, it's simply a means of exchange, and I think we fucked up the veneration for what Robert Anton Wilson dubs fun coupons, which are dollars and twenties and hundreds.
1:48:02
The other thing that you said earlier that I'm just thinking about right now is we still have this cultural lag where we believe that hours spent at an activity should in some way determine the value of that outcome, like the 10,000-hour thing and things like that.
1:48:24
Is it true that one must practice one's crap?
1:48:28
Of course it is, but I think that given the leverage that we now have through technology, through loose networks, through a variety of things that simply weren't available in the past, I'm happy to pay somebody who works for me at OSV if they can get done in an hour at the same level of quality a job that might take someone who's not as skilled 10 hours.
1:49:03
And this idea that it's the time in, that reminds me of tailorism a little bit where you're punching the clock and you owe me this number of hours. I think that's bullshit.
1:49:17
I think what you owe me is a fantastic work product and I honestly don't care how you come up with it.
1:49:25
So listen, we've already been going for, I can't believe this, two hours and I have only covered half the things I wanted to ask you about.
1:49:35
So I'm going to ask you right now, will you come back so I can cover the second half of my questions?
1:49:41
Dwarkesh Patel: It would be my privilege.
1:49:42
Jim O'Shaughnessy: Oh, terrific.
1:49:43
Dwarkesh Patel: It's been a pleasure.
1:49:45
I wasn't looking at the time either and I'm also shocked.
1:49:48
It just went by really fast.
1:49:49
It was just an engrossing conversation.
1:49:52
Jim O'Shaughnessy: It really was.
1:49:54
You are every bit as advertised.
1:49:56
Well, at the end of each of these, I always ask the same question, which is we're going to make you the emperor of the world for one day.
1:50:05
You can't kill anyone, you can't imprison anyone, but I am going to hand you a magical microphone and you can say two phrases into it and all 8 billion people, whenever their morning comes, they're going to wake up and they're going to think to themselves, "I have just had the two greatest thoughts ever and I'm going to act on them right now."
1:50:33
So in other words, you get to incept them.
1:50:36
What are you going to incept them with?
1:50:39
Dwarkesh Patel: That's a really interesting question.
1:50:43
I do think one thought that has been on my mind for the last few weeks while I've been reading these Johnson bios is that phrase we talked about at the beginning of this conversation, and that, I would probably try to plant in everybody I could, which is if you do everything and I mean everything, you will win.
1:51:01
So that is one that has really been on my mind and I would try to incept.
1:51:05
As for the second, let's see.
1:51:21
I'll think on that some more.
1:51:27
I'll three prepared for you the next time we talk.
1:51:29
Jim O'Shaughnessy: Fair enough.
1:51:31
Dwarkesh Patel: [inaudible].
1:51:32
Jim O'Shaughnessy: Fair enough, fair enough. Well, listen.
1:51:35
I really enjoyed both listening to your podcast and reading your stuff.
1:51:41
I think you're a pretty good example of that maxim.
1:51:46
If you do everything, you're going to win.
1:51:50
Babe Ruth is reputed to have said there's just no beating the fella who will never give up.
1:51:56
Dwarkesh Patel: Oh, that's great. That's great.
1:51:59
Well, Jim, it was a huge pleasure.
1:52:02
As I told you, I'm a fan of your podcast and I really admire the stuff you're doing with O'Shaughnessy Ventures, and obviously, the stuff you've done throughout your career, so a huge pleasure talking with you and a privilege being on your podcast.
1:52:13
Jim O'Shaughnessy: And the pleasure was mine.
1:52:15
Thank you and till next time.
1:52:17
Dwarkesh Patel: Excellent. Thanks.