Based Camp - October 12, 2023


Meet The VC Who Invests In High Schoolers


Episode Stats

Length

35 minutes

Words per Minute

196.88643

Word Count

6,998

Sentence Count

486

Misogynist Sentences

2

Hate Speech Sentences

7


Summary

Michael Gibson is the co-founder of the 1517 Fund, a venture capital fund that invests in young people, typically before they've even gone to college. In this episode, we talk about how he s been able to find and invest in so many young people and what he s learned along the way.


Transcript

00:00:00.000 Michael Gibson, he is the co-founder of the VC fund, the 1517 fund, which invest in young people,
00:00:06.840 typically before they've gone to college. How do you judge the competence of somebody who's young?
00:00:11.800 Yeah, we learned a lot. Well, when we started the fellowship, we had an application a lot like
00:00:17.040 colleges. We asked for test scores, GPA, what school you went to. And that was good at certainly
00:00:23.540 signaling cognitive ability, but we quickly learned it was not a strong predictor of success
00:00:28.880 out in the wild. And so we had to start looking for other things. There were even negative
00:00:33.540 correlations that were surprising. Would you like to know more?
00:00:37.300 Hello, today we are joined by Michael Gibson. He is the co-founder of the VC fund, the 1517 fund,
00:00:43.900 which is a game changer in terms of venture capital investment, because they invest in
00:00:48.920 young people, typically before they've gone to college, sometimes during. But he also wrote a
00:00:54.200 book that I've enjoyed very much called Paper Belt on Fire, which I really encourage you to
00:00:58.180 check out. But we're not going to be talking so much about the book today. We really want to get
00:01:02.540 into Michael's work with the 1517 fund, with how he spots young talent, with things he's learned from
00:01:09.660 his investments and the people he's worked with and the people he's found through this fund, because
00:01:13.580 I mean, oh my gosh, the talent you're reading, it's insane. So we're really excited to dive into
00:01:17.780 this and thank you so much for joining us. Yeah, thanks for having me.
00:01:21.600 So the biggest thing that I'm really curious about, because it's been a while now,
00:01:25.640 you know, you're like, you've been you've been doing this for years at this point. And you've
00:01:29.440 done a lot of hustling. I mean, like sleeping on couches, staying up all night, going to these
00:01:33.000 crazy young person parties. I couldn't do this. You know, like, young people stay up late. And I'm
00:01:37.360 like, my bedtimes at 830. Oh, my God, you're doing these.
00:01:40.280 Sorry, I got to take a little detour here. So I went on this trip to, I don't know,
00:01:45.320 somewhere in Central America, with a bunch of Peter Thiel Fellowship kids. And they like, they went out,
00:01:51.320 like, I hadn't gone to a party, like a club in years. I was like, maybe it's gotten better. Maybe
00:01:57.200 it's not as bad as I remember. And I get there, and I'm stuck there until 130 in the morning. And
00:02:02.660 it's loud, and it's sweaty, and it's gross. And it was just as pointless as it always was. And you
00:02:07.960 have to deal with this stuff, I think, professionally. Talk about how you get these young geniuses
00:02:15.380 interested in working with what you guys are doing. How do you sell yourself to them?
00:02:20.800 Man, well, that is certainly part of it. Yeah, it's funny is it's such a slippery,
00:02:25.380 tough craft that we're constantly reexamining the foundations of what we do. And one of the,
00:02:32.280 I guess, two different problems that we constantly wrestle with, or, you know, we,
00:02:37.800 I guess we're trying to figure out which problem we're operating in. One is, if you are a fisherman,
00:02:43.760 is it better to be in a well-stocked river or pond? So it's, you're one of those bears just
00:02:50.080 grabbing salmon because they're flying in your face, where in this case, the fish are, you know,
00:02:54.780 talented people building startups. Or is it better to focus on the craft of fishing, like being the
00:03:01.080 best, you know, it's like you could identify the one fish that's in the stagnant pond and find it and
00:03:07.020 fish it out. You know, that's, so this is like the two problems we struggle with. We're like, okay,
00:03:11.780 which one is it better to be? Is it better to find the location where just talented people are
00:03:17.900 and then figure out what they're working on? Or is it better to, you know, hone your skill,
00:03:23.280 pattern matching skill? Okay. Does this person have the right stuff and just, you know, go out there,
00:03:28.740 you know, looking for that. And so, so, so that is a trade-off or, you know, I can't, I guess I'm
00:03:34.820 saying it's two problems. It's just one problem. It's which one are we in? So to that end is,
00:03:39.000 yeah, I've been in hacker houses. I've lived in ecosystems and, you know, tried to go native
00:03:44.880 to the extent that I can, but now that I'm getting older, I've lost the steps. So maybe I,
00:03:50.180 like you said, it's tough to keep pace with a 21 year old.
00:03:54.000 Let's talk about what a hacker house is because our audience may not even know what this is. And
00:03:57.940 I think for young people who don't grow up or maybe live in like more rural environments,
00:04:02.380 it's useful to know that this other world exists that they can then move into, which is a quick path
00:04:07.180 to move up. Hacker houses are houses where near tech hubs, because it's often too expensive to
00:04:13.340 have a house yourself. A number of young people get together and put together a house. Now hacker
00:04:18.700 houses have variable levels of prestige. And so you want to make sure you get into a prestigious hacker
00:04:23.860 house, which typically means you're going to want to find someone in the hacker house ecosystem
00:04:27.240 and ask them in the city you're planning to move to typically San Francisco or New York,
00:04:32.060 if you're moving into hacker houses or London, I suppose, which are the most prestigious hacker
00:04:36.580 houses right now in this area. My brother and his wife actually ran a hacker house for a long time
00:04:41.140 in Silicon Valley. It was one of the high, high prestige ones. Okay. Yeah. Yeah. The icebreaker
00:04:46.840 was probably the one that everyone knew about during that time period. Yes. That was on the boat,
00:04:51.280 right? Yeah. Yeah. Some people got, so hacker houses are usually pretty weird. So they would,
00:04:55.480 the icebreaker, what they did is they got an old icebreaker. It's like a Norwegian icebreaker and
00:04:59.760 they converted it into a house that was on the pier by San Francisco and people would have parties there
00:05:05.520 and stuff. Can you talk about some of the more modern hacker houses you've seen, what they're like?
00:05:09.620 Well, it's interesting. Yeah. I wish, yeah, it'd be great if they had some intelligibility,
00:05:14.360 meaning you could find a list of hacker houses. You could find an ordering of, okay, here's what you
00:05:20.060 get out of these, but it's much more underground and not widely publicized. I guess you got to hear about
00:05:26.860 them through word of mouth or some Reddit chat group or something of that nature. Yeah. They come
00:05:32.480 and go too. And, and, and, and they're driven by the people who are managing them. There was one in
00:05:38.180 the mission that we helped start called mission control mission of San Francisco. That's a great name.
00:05:44.340 Yeah. What they didn't know, I guess, God, it's funny. I think there's like a sex club or S&M shop
00:05:49.600 called mission control. They didn't know that, but for them, yeah, it was more about these guys are
00:05:57.460 all software engineers, that type of hacker. There were 10 people at a time living in the house. And
00:06:03.700 sometimes people work at companies. Sometimes they start companies. They tend to be very creative.
00:06:08.800 They're, they're almost like a studio artist studio in a sense of building things. Some people are
00:06:14.040 working, they change, they swap, they come in and out. So yeah, we, we, we, I know of a few in different
00:06:19.820 places. We're starting to see more now, like in, at the university. Oh, they tend to also be associated
00:06:26.160 with universities. Like it'll be a university town where you see these things pop up. And there were
00:06:30.480 some students at the university of Michigan recently who started a house devoted to brain computer
00:06:36.400 interfaces, that issue. So I thought that was cool. Cause it wasn't just, you know, yeah. You know,
00:06:41.120 like me today, I'm so San Francisco, I've got the hoodie on. It was not the coding, you know,
00:06:46.680 the code monkey wearing a hoodie. It's they're actually working on some, on hardcore science,
00:06:52.160 which, which is cool to see. So it's tough for me. I'd like, I do want to know about these places
00:06:57.800 because they can be gravity wells for talent, but on the other hand, they're not well advertised. So
00:07:03.080 you got to hear about them through word of mouth. And another thing that used to be a real gravity
00:07:07.640 well for talent, I don't know if it still is, is maker spaces. Sure. Yeah. I would also
00:07:11.020 look up if you have a city, so they're called hacker spaces, Baker house spaces, or you can look
00:07:15.480 for bio hacker like labs, which cities, which will have most of the equipment you need to do this
00:07:21.440 sort of more advanced science stuff. And they're typically sort of like all of our guard. The one that
00:07:25.460 I was really into back in the day was the hacker dojo. Yes. I was just going to say the hacker
00:07:30.000 dojo. Yeah. I used to hang out there every, every party, every week. It was fantastic. It was really
00:07:35.920 based. If you've ever seen the movie hackers, like the 19. So I don't think that that movie
00:07:41.220 was based on a real culture that exists, but I think that generations of nerds grew up with
00:07:45.220 that movie and they basically recreated a funny thing when you were mentioning about, Oh, this
00:07:50.600 is the name of a sex place. I was like, yeah, but a lot of hacker houses do have regular.
00:07:55.320 That's true. Yeah. Well, they tend to be very counter-cultural. They have that. Yeah. That's
00:08:01.820 so funny. Yeah. Hackers. Was that the Angelina Jolie movie? Yeah. Yeah. Okay. Well worth a watch.
00:08:07.060 It is. One of the things I love in movies about computer engineers is they always face the problem
00:08:13.620 of how to dramatize or visualize what it is to work on a computer. And that one was great because it
00:08:20.200 was like, they're actually running through like a street of code or something. That's like a city.
00:08:24.500 Yeah. And Hacker Dojo, by the way, for people who didn't know, so the old version of Hacker Dojo,
00:08:28.600 there's like a new version that's really corporate and boring, but the old one, what they had bought
00:08:31.680 was an old stained glass show factory because it was where they were trying to sell stained glass.
00:08:36.860 So like the whole thing was like weird and designed and like hanging platforms and everything. It was
00:08:42.220 nuts and big mechanical beasts that they had beat that they would take out to maker fairs and stuff.
00:08:47.080 But okay. So next, tell me about the type of person that you're looking at, because when you're
00:08:50.320 talking to young people, how do you judge the competence of somebody who's young and how do
00:08:55.280 you know when they're like too arrogant? And can you give me any of the weird stories you've had
00:09:00.040 dealing with these young geniuses? Yeah, we learned a lot. And I guess it is a lot like
00:09:06.020 pattern recognition as it relates to, let's say, computer vision or deep learning in the sense of
00:09:12.360 you have a data set and then your algorithm has to train on that. Deep learning operates in a black
00:09:18.480 box. So oftentimes it's, it's shooting out answers and you can't figure out why it arrived at that
00:09:24.440 answer. Well, I think human expert intuition is quite similar because you're building up a algorithm
00:09:31.600 across this data set. So what's our algorithm? Well, when we started the fellowship, we had an
00:09:37.480 application a lot like colleges. We asked for test scores, GPA, what school you went to. And that was
00:09:43.780 good at, at certainly signaling cognitive ability, but we quickly learned it was not a strong predictor
00:09:49.540 of success out in the wild. And so we had to start looking for other things. There were even negative
00:09:55.020 correlations that were surprising. So one of them, the funnier ones to me was like the winners of the
00:10:00.300 Intel science award tended to fare poorly as entrepreneurs. And, and why? Well, okay. It's because
00:10:07.420 to win those awards, you have to be a good like ESG salesperson, not a innovator. It's just who can,
00:10:15.140 you know, signal the most virtue for a committee rather than actually build something. So over time,
00:10:21.620 yeah, we started to develop our rules of thumb. Certainly the traits we look for can't guarantee
00:10:26.660 success, but they, they became contributors to success. Like one of the weird esoteric ones is
00:10:32.540 something we call insider outsider. This is from Peter Thiel's work with René Girard. So Peter studied
00:10:38.920 philosophy or literature with René Girard. He's a French literary theorist who became a bit of an
00:10:45.440 anthropologist and historian. And Girard was obsessed with crowd dynamics, witch hunts, mobs,
00:10:52.440 and scapegoats. And he has a monograph on the scapegoat in which he canvases the world mythologies
00:10:58.980 and religions and examines all these episodes where the crowd picked a scapegoat and sacrifice
00:11:05.220 them. Or, or, you know, sometimes what's interesting is that the hero is often a scapegoat who has
00:11:10.620 resisted sacrifice. And so for Peter, this became a way of looking for founder, a trait to look at for
00:11:19.060 founders and people to hire. And what Girard found was like the people that the crowd doesn't just pick
00:11:25.360 a complete foreigner to sacrifice because if there's a social crisis at hand and they need
00:11:30.500 to blame someone, you can't just grab a foreigner who couldn't possibly have anything to do with it.
00:11:35.660 On the other hand, you can't pick the king's right hand man, you know, that's just too close to the
00:11:40.300 center of things. So oftentimes that scapegoat is this boundary figure who somehow paradoxically
00:11:46.220 is both an insider and an outsider. And you can see this. I mean, think about Christ,
00:11:51.240 you know, classic scapegoat story is he's, he's on the one hand, Jewish preacher. And on the other
00:11:58.200 hand, you know, excommunicated by the Pharisees and so on. You can see this in the myth of Oedipus
00:12:03.480 where, or the play Oedipus where, you know, Oedipus is, he is, there is a plague that is destroying
00:12:11.220 the city and he, he sets out to discover its cause. He is the king. He thinks he was born in a foreign
00:12:18.020 country. Actually, he turns out he was born in the city, but, but because he came from somewhere
00:12:23.120 else, it's like, he's both an insider and an outsider. So Peter looked at the, you know, when
00:12:27.300 he examines, when he's looking at a founder, so on, he's always looking for some kind of insider
00:12:32.520 outsider story. One easy, clear example is let's say immigrants. So immigrants who come to the United
00:12:39.360 States, there's a long tradition of creative immigrants in Silicon Valley who have done great
00:12:43.320 things. And I think it's this insider outsider dimension where on the one hand, they are U S
00:12:48.840 citizens or green card holders, but on the other, they are outsiders. You know, they're new to the
00:12:53.600 country. They might see things in different ways. Maybe I myself am an insider outsider. And I was
00:13:00.500 working towards a PhD. I spent many, many years in grad school. I've seen the insides of the temple
00:13:06.400 of academia. And, and, and yet I, I left, I, I dropped out and became a heretic. So maybe that's,
00:13:13.960 you know, possibly why Peter hired me. So, so that insider outsider thing is something we're,
00:13:19.000 we're always looking for. And, and, and I like talking about it because it's just so weird
00:13:22.700 because it comes from French literary theory. And then the other thing is, yeah, you got to have the,
00:13:27.680 the know-how, the, the IQ and, and, and EQ to work with customers and co-founders and so on.
00:13:34.720 But no one thinks about, you know, that dimension. So that's why, you know, I think it's worth
00:13:38.880 meditating on. What's really interesting is I, go ahead, Malcolm. Well, I want to provide an
00:13:43.940 alternate theory as to why insider outsiders do so well. What you're actually capturing with
00:13:50.340 insider outsiders is to, to be an insider, to be a competent or move up within the inside system.
00:13:56.320 That's typically a measurement of just general, like EQ, IQ, everything like that. To be an outsider,
00:14:02.260 to be willing to outside yourself, when you have already risen within a traditional power structure,
00:14:08.820 to any extent, you have to have enormous initiative, a willingness to take calculated risk,
00:14:15.440 confidence in yourself, and belief that you understand something about the way the world is
00:14:20.400 working that the insider system doesn't see yet. And so, you know, this is seen with immigrants,
00:14:25.100 right? To be an immigrant, you have to have an enormous amount of individual initiative,
00:14:29.740 individual belief in yourself, everything like that. Well, to be an immigrant with-
00:14:34.360 Look, that could even be a genetic selection effect, right? I mean, one theory about the
00:14:38.380 American frontier is that it was filled by people who had that risk-loving gene to just set out to
00:14:43.840 the frontier and face nature or- We have another episode on this called Genetic Vortexes. And we
00:14:49.620 talk specifically about Silicon Valley. And we say it's probably not a surprise that Silicon Valley,
00:14:54.660 as we understand it, started, that venture capital started in the same area that people were
00:14:58.780 coming to during the gold rush, which was selecting specifically for high risk, high reward focused
00:15:05.600 individuals. Right. Yeah. And then, and that, okay. To move on to another trait we look for,
00:15:11.200 sometimes I call this edge control and which I take from skiing, snowboarding, motorcycle racing,
00:15:17.300 because there is a, there, look, there's a, there's a, there's some amount of courage that's
00:15:21.300 necessary to want to do something new and different. And, and to challenge the status quo in
00:15:28.580 majority opinion. But the, the thing is, it's not just like an extreme sport though, where you jump
00:15:33.920 out of the airplane once and, and get that adrenaline thrill. It's an every day, day after
00:15:39.480 day. Are you prepared to, you know, negotiate that boundary between chaos and control on a daily basis?
00:15:47.560 And I think it takes a certain type of person to do it. It dawned on me that also that, you know,
00:15:52.720 I say I like edge cause that signifies danger and risk control is okay, but you got to keep
00:15:58.500 everything in order. And so with the skiing example, you can't just go down a black diamond,
00:16:03.480 like the fastest skier doesn't win Olympics and two Olympics. So there's some Italian phrase that's,
00:16:09.640 you know, the best skier isn't the fastest skier because that person crashes and breaks a leg and has
00:16:13.900 a career ending injury. So they don't get to participate in all the races they could have after that.
00:16:18.780 So it's like the best skier is the one who goes as fast as possible while surviving.
00:16:22.920 And I think there's something to that in startups where there's, there are people who,
00:16:26.220 who push the edge of things, but not too much where they blow up the company. And on the other
00:16:30.960 hand, they're not so conservative that they don't experiment or do anything at all.
00:16:35.140 So what I really love about what you just said, cause it reminds me of something I've seen.
00:16:39.060 And I've consistently seen this in people who end up being successful is you don't want to be,
00:16:43.280 gosh, what's the word? It's from the family guy episode of South Park.
00:16:46.480 Okay.
00:16:47.140 Or something pushing balls. Right.
00:16:49.300 Yeah.
00:16:50.240 And they, they stopped working whenever you would take a single idea ball out of the tank.
00:16:54.800 Oh, right, right, right. Yes.
00:16:56.440 Oh, manatees, right?
00:16:58.160 Manatees.
00:16:58.540 Yeah. You don't want to be a manatee, we say.
00:17:00.440 You don't want to be a manatee.
00:17:01.960 Because the manatees in this episode, they would stop coming up with ideas.
00:17:05.040 They'd stop producing episodes the moment you took one idea ball out of the tank.
00:17:08.960 And yet the people who I find who I think represent the highest likelihood of like actual success,
00:17:14.760 especially when I'm talking about young people, is they love surfing on the edge of controversial issues.
00:17:20.060 But they never go over the edge to the point where they would get canceled or anything like that.
00:17:25.560 You don't want to understand the game that they're playing.
00:17:29.640 And I'm going to be honest, this is a game that we really like to play in our videos.
00:17:32.660 I think people see it.
00:17:33.940 A great example of an individual who's doing this more and more now.
00:17:36.680 And I think we're going to see great things for him in the future.
00:17:38.560 He's actually, I think you guys identified him.
00:17:40.760 He might have been a Teal fellow or he might have been something else.
00:17:43.800 But it's the what if alt-hist guy.
00:17:45.660 He runs another popular.
00:17:46.480 Oh, yeah, yeah.
00:17:47.420 Great.
00:17:48.060 Yeah.
00:17:48.360 Definitely.
00:17:50.320 He definitely is really good at getting right up next to how controversial intellectuals might be without ever going over the edge.
00:17:56.700 And I think that that is a really good indicator of somebody who has a like of living on the edge,
00:18:03.680 but doesn't actually ever want to do real risk.
00:18:06.240 And that's what's true about good entrepreneurs, as it's been said.
00:18:09.460 Entrepreneurs are risk mitigators.
00:18:12.040 They take an idea that is big or something like that.
00:18:14.900 And then they say, how can I mitigate all of the risk associated with this idea?
00:18:19.480 Yeah.
00:18:19.640 They're not just going straight down the mountain as fast as they can and crashing into a tree, right?
00:18:25.620 There's a way to climb the wall.
00:18:27.380 I don't know the analogy, but there's something where there's a plan.
00:18:30.320 And, you know, actually, one book I read this week just came out was the new Walter Isaacson biography of Elon Musk.
00:18:38.900 Oh, I'm in the middle of that.
00:18:40.360 It's so fun.
00:18:41.740 God, it's great.
00:18:42.540 Yeah, really fascinating.
00:18:43.800 I love how, you know, Isaacson just had so much access to Musk.
00:18:48.720 Instinct, yeah.
00:18:49.560 You just see Musk for everything he is at work and in his personal life, which is wonderful.
00:18:55.920 But there's this, I noticed, I guess in production meetings or whenever they're discussing assembly lines, Elon Musk has this thing he just calls the algorithm, these five steps about the processes.
00:19:06.720 And one of them is to constantly delete unnecessary superfluous things.
00:19:12.300 But how do you know if it's necessary?
00:19:14.480 Well, you've got to delete it.
00:19:15.500 And if the thing's not working, then you bring it back.
00:19:18.640 Yeah, and if you're not adding at least 10% back, you're not deleting enough.
00:19:21.480 Yeah, so if you're not adding 10% back, then you're not deleting enough.
00:19:25.260 And that to me is a good example of like how to negotiate these boundaries of the known and the unknown is like you're going to have to go back and forth.
00:19:32.600 And if you're not doing some amount of deleting and then bringing back, you're not doing it enough.
00:19:37.280 And likewise, I think flirting with controversial ideas, when you're getting up on the edge of these things, it's like you're, it's so hard to maintain the balance and hit that edge.
00:19:45.480 So you're like, sometimes you go a little too far.
00:19:47.840 Sometimes you're coming back.
00:19:50.060 The personal assistant story, that's from Elon Musk, right, Simone?
00:19:53.680 What personal assistant story?
00:19:55.640 I see you remember the story.
00:19:56.700 It was one billionaire anyway, where his personal assistant was like, I want some more money.
00:20:00.940 Like I want equity.
00:20:02.040 Oh, that was from the 2015 biography of Elon Musk.
00:20:05.320 No, no, no.
00:20:06.440 That's not from the new.
00:20:08.280 The Ashley Vance.
00:20:09.960 But it is a good example of what he's talking about, where they're like, I want some equity in the stuff you're doing.
00:20:15.080 And he goes, well, you do seem to provide a lot of value.
00:20:17.360 Okay, let's try this.
00:20:18.480 How about you stop working for me for a month and I see if I miss you?
00:20:21.640 Oh, my God.
00:20:22.480 Yes.
00:20:22.960 That's great.
00:20:25.060 It is smart.
00:20:26.120 It is smart.
00:20:26.660 And she also didn't have a job when she came back.
00:20:29.240 It is, I mean, I like that ruthless optimization.
00:20:32.860 I also love this way of looking, like these little weird correlatory details.
00:20:37.300 It oddly reminds me of autism diagnoses because there's like all the stuff that they do to diagnose people with autism.
00:20:42.500 But then there are these like weird hints that like, oh, that's a sign.
00:20:46.220 If a kid lies on the floor and they like move a car back and forth, just look at the wheels and just do that for a long time.
00:20:52.420 They're like, that's a sign.
00:20:53.880 Or if you take off their shoes and they walk on their tiptoes, they're like, that's a sign.
00:20:57.400 I've seen the tiptoe thing.
00:20:58.720 Tiptoe walk.
00:20:59.740 And so it's like you have the autism cues for brilliant talent.
00:21:04.120 One thing I worry about, though, like with talent is there are many people that we even know of now, like who have grown up in our generation, who like were the wunderkind of their time.
00:21:15.520 Yep.
00:21:16.340 And then they flamed out, like they fell in a wrong direction.
00:21:22.780 They just sort of got indulgent.
00:21:24.380 They stopped working.
00:21:25.120 Have you found any predictors for that grit that just keeps people working at it?
00:21:30.520 Maybe something else.
00:21:32.580 Yeah.
00:21:32.740 That's the one of the challenging things is with the receiving applications and trying to judge people.
00:21:39.840 I often use the metaphor that it's like fruit.
00:21:42.080 You starts off fresh and gets stale or rotten fast because you it's here's a snapshot.
00:21:47.160 And then maybe they change or do something else that can be positive or negative.
00:21:51.040 So what we decided is we just the best thing we can do is try to get to know people over time.
00:21:56.060 And if we have multiple interactions with someone on some level, we'll get a better sense of do they execute?
00:22:02.420 Do they push through?
00:22:03.620 One thing we do at the 1517 now is we give out 1K grants to people.
00:22:07.660 If someone says they want to build a prototype, but they just need to buy some parts, we'll kick them a thousand bucks.
00:22:13.120 Oftentimes that turns into nothing.
00:22:15.540 But what we get out of it is a chance to interact with someone over a short period of time.
00:22:20.220 It can be two months, three months.
00:22:21.620 They get to work with us and that gives us more information about, okay, do they follow through with what they say they're going to do?
00:22:27.880 Other than that, you have to rely on stories.
00:22:30.000 But those are like college admissions essays.
00:22:32.780 They all follow the same pattern.
00:22:33.980 Oh, you know, I had this tragedy.
00:22:36.980 I had this setback.
00:22:37.960 And then I dug within during the dark night of the soul and came back and found the answer.
00:22:42.800 Yeah.
00:22:43.060 So those aren't as believable.
00:22:45.160 It's best if you can actually see over time, which is tough.
00:22:49.580 Some pattern recognition I've seen from the group that we were in.
00:22:51.780 Because I was mentioning in the other interview we did that if you look at this old early EA, less wrong rationalist group, many of them grew into very influential people in today's at least scientific and economic ecosystem.
00:23:02.240 I think the biggest thing that I saw as a predictor, which really aligns with what you're saying, that they are going to spin out and do nothing even if they're known as very smart, is are they task-oriented with money that's given to them?
00:23:15.060 If somebody gives them a lot of money and then they use it to write a Harry Potter fan fiction, they're probably going to end up doing nothing with their life and just degrading AI research for an entire generation.
00:23:26.180 I don't mean to be too spicy here.
00:23:28.340 But what I'm saying is, I notice this repeatedly, is that some individuals, when they would get money or when they would get leeway, they would spend it on sort of not exactly what they had originally envisioned.
00:23:40.420 While the people who were very task-oriented, especially if they were willing to be task-oriented on boring-ish ideas, like ideas that might not be like, oh, I want to make shipping freight marginally less expensive or something like that.
00:23:54.360 Even if they didn't succeed with that project, they typically eventually succeeded with something.
00:23:58.340 That's a good point.
00:24:00.200 I think one thing we noticed, too, was the people who could set their own goals.
00:24:04.880 And homeschoolers were best at this right away.
00:24:08.300 They could schedule their day.
00:24:09.540 They could move in and out of the world, make new friends out in the real world.
00:24:14.280 Whereas people who were even high-achieving students at Ivy League schools, since their whole life has been structured for 16 years and they've received assignments and they've completed them well, it's a whole other world to just step into, hey, what do I do with my day?
00:24:30.660 I have no schedule.
00:24:31.540 How do I organize this?
00:24:32.680 And I saw some people get paralyzed because there was a transition period where they didn't know how to set their own schedule and goals or didn't feel comfortable doing it in the same way that a homeschooler would.
00:24:42.780 Do you feel homeschoolers are better?
00:24:45.020 Like within your program, do they have an edge over the Harvard kids?
00:24:48.340 Yeah, we haven't done a count in a while, but I do recall in the early days of the fellowship that the homeschooler, or at least people who had some period of homeschooling.
00:24:57.420 So it wasn't just like the full education, but it could be two or three years, especially in the high school period.
00:25:03.120 Those people tended to be high-performing.
00:25:06.540 There was a strong correlation there.
00:25:08.780 Of course, I don't know.
00:25:09.540 We didn't look at all the homeschoolers in the world.
00:25:11.460 But the ones who applied, for sure, were very strong candidates.
00:25:17.920 So parents, homeschooling still has high marks for the people who are the world experts on judging you.
00:25:24.220 Well, to go back to the point about courage and grit, schools don't teach that stuff.
00:25:31.300 Maybe we don't even know how to impart that.
00:25:33.560 How would you run a class on challenging the status quo and majority opinion or disobedience?
00:25:40.460 If you had a class on disobedience, the first lesson should be you don't show up, right?
00:25:44.760 I love that.
00:25:47.500 You grade them based on whether or not they show up.
00:25:50.500 Yeah, you failed.
00:25:51.420 If you show up, you let them know you failed.
00:25:53.980 So one thing I'd love to close this particular interview with is the craziest story of an entrepreneur or something like that that you encountered that only could have happened given the age of the people that you were interacting with.
00:26:08.020 Well, one thing the young have that's just a general advantage that I've seen is that they have no big duties and obligations that older people accumulate, like mortgages, pets, spouses and children.
00:26:26.480 So the 22-year-old who can just sleep on a couch and work night and day, weekends, that gives an advantage of speed and hard work.
00:26:39.000 So that's just independent of that.
00:26:41.300 But in terms of, let's see, some people I've worked with, I think there's just also something to, people don't want to admit this,
00:26:51.560 but there's a biological life cycle to our creativity and our fluid intelligence.
00:26:56.860 And I think some of the people I've met are certainly far ahead of the curve on IQ and creativity,
00:27:03.540 but they have to accumulate some amount of knowledge in a field, but they still have fresh eyes when they come to it and they've got that speed of mind.
00:27:11.140 And so they're able to see things that I guess, you know, more established people aren't seeing.
00:27:16.700 So, you know, the example of that could be Vitalik Buterin or Austin Russell, you know, they, I don't want to say they discovered what they discovered because they were young,
00:27:26.020 but certainly they had the energy and the fresh mind to see things that, that, you know, the more established people in their field weren't thinking about.
00:27:34.260 Or in the case of the blockchain, I mean, maybe there's something where younger people are willing to experiment more with weird stuff and think about it.
00:27:41.160 But that's very, very strange. But to back to the larger point, I think it is true.
00:27:45.520 You look at the psychological research on achievement, especially as measured by things like in the arts,
00:27:52.380 it could be, you know, how many masterpieces someone has or in science, how many papers they publish and what papers win them,
00:27:59.660 the Nobel prize and all of that. And there's pretty clear, you know,
00:28:03.660 there's a rise in the twenties and a peak in the thirties and then people taper off in middle age and,
00:28:10.460 and each field has different averages, but it's pretty constant that people are very productive in their youth.
00:28:17.460 So is that they aren't later on. And, and I, I'll just say,
00:28:20.220 I hate as a society that we don't admit this because it's twenties, you know,
00:28:25.740 yeah, exactly.
00:28:27.100 In his twenties when he came up with all this. Yeah.
00:28:29.060 Yeah. In the same way that I guess it's like feminism told women, you know,
00:28:33.860 they could have it all or, or they could wait.
00:28:36.240 And then there's just this biological reality that it becomes harder and harder to have kids in your thirties and forties.
00:28:41.460 So, you know, I think it's a disservice to tell women that they can, they can wait.
00:28:46.300 They should really think about that. I think it should be something, okay.
00:28:49.640 They don't, I'm not saying everyone has to have kids, although it would be great if they did.
00:28:53.440 But the, but on the other hand, they should know, Hey, there's this window where this is possible.
00:29:00.500 And, you know, unless we invent new things, it's something you have to reckon with.
00:29:05.220 Well, that's why we wrote all our books when we were still young, but yeah, no, I, I actually,
00:29:10.000 there's a concept that we have brought up in some of our work before that hasn't been talked about in the mainstream society,
00:29:16.620 but I think it's a way that you can sort of test this.
00:29:19.060 We call it the concept of brain rot and it seems to happen to some individuals as they get older or it seems to happen to everyone eventually.
00:29:26.180 But the core sign of it in an individual that we use to measure how much brain rot somebody has is in a social situation,
00:29:34.340 when they're interacting with you, how much of the time or how many times do they bring up the self narrative?
00:29:40.460 So people with a high degree of brain rot will constantly be in self narrative loops.
00:29:46.680 Like this is what I was doing, or this is who I am, or this is the type of person I am.
00:29:52.820 Whereas people without brain rot are typically focused on efficacious ideas.
00:29:57.760 Like what's happening in society and how do I affect it?
00:30:01.480 Yeah.
00:30:02.440 Huh.
00:30:02.660 I'll have to pay attention more.
00:30:04.520 I think, yeah, that's interesting.
00:30:05.960 The brain rot.
00:30:06.980 I thought this is part of the longevity research.
00:30:08.680 I think no one is really approaching enough or tackling or scratching out enough.
00:30:13.240 Well, they don't want to.
00:30:14.100 I mean, you should know that we're pretty against life extension.
00:30:17.060 Okay.
00:30:17.620 Yeah.
00:30:18.180 It's an inevitability, not just of our biology, but of the way that ideas sort of begin.
00:30:23.840 We think it's a feature, not a bug.
00:30:26.020 Yeah.
00:30:26.300 You just accumulate all these categories and concepts and frameworks.
00:30:30.060 And then it's tough to, once they're set in at 70, you're not, you're so resistant to new concepts.
00:30:38.040 Well, and you're also incentivized to crunch yourself in more power.
00:30:41.280 You're not as important to redistribute to begin new.
00:30:43.940 Yeah.
00:30:44.300 You're not going to belong to what you have.
00:30:45.380 And you're going to resist anyone who's trying to change the world order.
00:30:48.000 And we need that.
00:30:49.540 Yeah.
00:30:49.700 It also be by self-narratives that are important to them.
00:30:51.480 Yeah.
00:30:51.680 Because if they're in this position of power, they need to constantly reiterate self-narratives that reinforce this position of power they have.
00:30:58.360 Right.
00:30:58.920 Yeah.
00:30:59.100 The one counter example.
00:31:00.840 We've met people in their 20s who have brain rot.
00:31:03.060 Yeah.
00:31:03.260 And we've met people who in their 90s don't.
00:31:05.780 Right.
00:31:05.920 And I think with aging, which is so underrated with so many things, it's just use it or lose it.
00:31:11.200 Like it's shown with cognitive performance.
00:31:13.300 It's shown with like different like organs.
00:31:15.780 I don't think it's true.
00:31:16.420 I think it's true.
00:31:17.100 I think it's true.
00:31:17.160 I think it's that people who don't have it aren't using it.
00:31:19.840 And so anyway, Michael was going to say something.
00:31:21.680 Oh, the one counterexample people bring up when it comes to productivity in late age is the mathematician Paul Erdos.
00:31:28.300 He's this guy.
00:31:29.380 He's like the Kevin Bacon.
00:31:30.880 There are mathematicians with an Erdos number where it's like how many people are in the network?
00:31:37.080 Are you away from a paper from Erdos or something?
00:31:39.340 Apparently.
00:31:39.880 That's funny.
00:31:41.100 I forget exactly how the index works.
00:31:43.220 But at any rate, he apparently was very productive into his 80s, maybe even his 90s.
00:31:48.000 But what stands out about him is that he was fearless when it came to dropping a field in mathematics and then just moving to a new one late in life.
00:31:56.980 So it's like he reached, you know, I guess he hit the point.
00:32:00.920 He knew when when his mind was saturated in a particular topic and then he just let it go.
00:32:05.900 And he had beginner's mind all over again and something new.
00:32:08.840 And so I think there to the brain rot is like there's this clutching at identity, like you're known as this, you know, string theorist or macroeconomist.
00:32:18.720 And there's no way at 55, all of a sudden you're going to give up macroeconomics and suddenly start working on some other field where you'll have to be a beginner and suck again.
00:32:28.940 Yeah, maybe this is also why parents are now so strongly dissuaded from saying anything about children's character.
00:32:35.520 Like now everyone says, never say, oh, you're so smart.
00:32:38.680 Just say, well, you tried so hard.
00:32:40.040 That was so clever what you did.
00:32:41.840 Because if you have a child who starts to identify as smart, then they're more likely to not even try to do challenging things because the challenging thing might disprove their smartness.
00:32:50.560 That's right.
00:32:50.840 There's a complacency and a protectiveness that that gets attached to that identity.
00:32:56.000 Yeah, that leads to lossification.
00:32:58.260 So any sort of like attachment to identity is very dangerous.
00:33:01.800 Yeah, very much so.
00:33:04.440 Well, this conversation has been spectacular.
00:33:08.060 I'm so glad you joined us.
00:33:09.580 I know.
00:33:10.020 We can keep going on time flies.
00:33:13.120 My understanding of things a lot.
00:33:15.160 And it caused me to reflect on a lot of things that I hadn't reflected on in terms of how we look for students and what we try to optimize for with our own kids.
00:33:23.780 Yeah.
00:33:23.980 And one of the things that I'll leave with, I guess, is like talent identification is hard.
00:33:29.340 It's something we've been doing.
00:33:31.380 But what I wish we knew more about was development is like back to that courage question.
00:33:36.640 Okay, how could we inculcate courage in young people?
00:33:40.180 Because it just seems like it's really hard to do and no one's doing it.
00:33:42.880 Yeah, well, and to that end, if we have young viewers listening to this, you know, do look into local hacker spaces.
00:33:50.280 Do look into moving to a hacker house for a while.
00:33:52.840 Do look into reaching out to your heroes because they're often a lot more receptive than you would imagine.
00:33:57.600 And it's a good way, you know, it is this sort of immigrant mindset, which is, okay, this thing is crazy and would change everything for me, but I'm going to go out and do it.
00:34:07.800 And I would encourage, because I think sometimes you grow up in an environment where you don't even realize that's an option.
00:34:12.760 And then, you know, you could just email them.
00:34:15.900 You could just move to San Francisco.
00:34:18.780 If you actually are competent, you will start being invited to these parties very quickly.
00:34:24.580 Absolutely.
00:34:25.540 A lot of on-ramps in San Francisco and cities that other cities don't have, like as great as Austin and Miami are, I think they lack a lot of the on-ramps that San Francisco has.
00:34:37.280 Nobody goes to Miami thinking, I'm going to work hard and build my future.
00:34:41.280 I want to be clear.
00:34:43.540 It doesn't have as many on-ramps as it used to.
00:34:45.440 Now, most of the on-ramps I've seen to this cultural group are actually online on-ramps, like small Discord threads of like nerds and stuff.
00:34:53.880 That is where I see the actual on-ramps occurring, but it is, it used to be that San Francisco was where you would go to do this.
00:35:00.700 Yep.
00:35:01.040 Yep.
00:35:02.680 Anyway.
00:35:03.340 Well, I enjoyed the conversation.
00:35:04.880 Thanks for having me.
00:35:05.240 I loved it too.
00:35:06.380 And let's hope San Francisco can ascend from its desiccated state right now.
00:35:10.780 I don't know if it ever will, but it might.
00:35:13.460 Well, we can only hope.
00:35:15.300 Let us pray.
00:35:16.700 Yes.
00:35:17.260 Oh, Michael, thank you so much.
00:35:18.460 And everyone, please make sure you check out 1517.com and also Paperbell on Fire.
00:35:23.440 Oh, and you're also on Twitter, but you're not Michael Gibson.
00:35:25.840 You are William underscore Blake.
00:35:27.760 So check him out on Twitter as well.
00:35:30.280 All right.
00:35:30.780 Thanks.
00:35:31.100 Bye.
00:35:31.700 Bye.
00:35:32.380 Bye.