0:00
If you looked at the growth of population, Malus nailed it.
Search this video
0:01
What he didn't nail, and I view this as a bug in human OS, he thought that the ability to feed that population was fixed.
0:12
Every model is going to be a simplification of reality.
0:16
And the question becomes, what do we want it for?
0:18
So like with weather modeling, often times we just throw more and more complexity into these things, and they've actually worked better and better over time.
0:26
But when it comes to necessarily like certain ideas around like intuitive understanding, trying to put the entire weather model in your head is basically an exercise in futility.
0:37
There's no way you're going to understand that kind of thing. Well, hello everyone.
0:43
It's Jim Oanosy with yet another Infinite Loops.
0:46
I was really looking forward to today's guest because it seems like we are traveling in very similar circles and yet Sam Arbsman and I have not met one another.
0:59
Sam uh like I'm a little daunted to be honest to be even talking to you because I don't think I'm smart enough to even come up with good questions.
1:05
Sam is a complexity scientist and writer obsessed with seemingly unrelated ideas covering science and technology.
1:13
actually not covering connecting them.
1:17
He's the author of three books, Over Complicated Technology at the Limits of Comprehension, The Half-Life of Facts, and his newest, The Magic Life of Code.
1:29
He's also, I mean, goodness, if I'm reminded of the Mark Twain where the guy went on and on introducing him, and he took like 40 minutes uh uh you know, doing all the things that Twain had accomplished.
1:41
uh and uh he finally got to Twain and and Twain said, "Well, I've been left five minutes to make my remarks, so I will give my address."
1:48
And then he gave his address where he lived in Hartford.
1:52
But I mean, honestly, you're the scientist in residence at Lux Capital.
1:56
You have a PhD in computational biology.
1:59
And like I love your origin story, too.
2:02
Like you're a superhero in my eyes. That is too kind.
2:06
And your origin story is fabulous in that your grandfather, who was a retired dentist and artist, gave you a huge bag of science fiction books to take with you to summer camp and you Dune was still being serialized then.
2:23
Like that is really cool.
2:23
Was like what what happened when did did your mind explode or or tell tell us the story. >> Yeah.
2:32
So, so, yes, my grandfather, I mean, he he's been reading science fiction since like basically like the modern dawn of the genre. Like, I mean, yeah.
2:40
And so, and he did not give me the serialized versions of Dune.
2:42
Um, that was well before my time, but he he definitely read Dune um when it was in a magazine.
2:48
Um, he I mean, he gave me uh his initial copy of the Foundation trilogy. So, I have that one.
2:54
I actually still I still have it.
2:55
Um, and yeah, and he would and he was a very longtime subscriber to to analog science fiction.
3:02
in fact, probably I think it had a different name at some point.
3:04
I'm sure he probably subscribed to it when it was the the original term uh the original title.
3:09
And uh yeah, and what he would do is after he would read all the issues, he would then give me all the old ones in shopping bags and then say, "Okay, go take these and I would take them to summer camp and read them."
3:18
And and uh yeah, it was I between those magazines and him mentioning all these like other reading suggestions. Uh yeah, it was amazing.
3:27
It was just kind of wild to see especially uh and he I think he introduced me to a lot of kind of like the golden age sci-fi of like >> like Azimov and Heinline and Arthur C.
3:40
Clark and those like that time period as well as later time periods as well.
3:42
And it was just fantastic to see kind of how people were envisioning what the future meant.
3:48
meant. And the truth is actually so in the analog science fiction magazines in addition to short stories and nollas and things like that there were also essays like there would be this I think it was called like the science fact essay and
4:00
and I remember reading those because it was people talking about just weird things kind of at the edges of science like someone would be like oh here's some interesting theory on how to actually make a warp drive a real thing
4:11
and then I devoured that and then some other person talking about some weird moment in history during the Middle Ages where some weird happened and maybe that meant something around aliens and like and of course it was super speculative
4:22
and super weird but it just opened my eyes to this collapsing of science and fiction and thinking about the future and history and all these different ideas and yeah it was incredibly eye opening um and actually as a as as a fun thing also related to my grandfather. in
4:36
in addition to reading sci-fi, he also read like science.
4:40
It's like science fact as well a lot.
4:43
And he um so he I remember when I was little, he would always have popular science magazine and and I would when it was over at their house, I would I would read it periodically.
4:52
And later on, he mentioned to me just in passing, he's like, "Oh yeah, I started reading it when I was in high school."
4:59
And and then I realized at that point he had been reading reading it for I think like over 70 years or whatever it was and I had a friend at the time who was working for Popular Science and I emailed him.
5:11
I said I think I found your longest like like the oldest like longest living reader of the magazine and they ended up actually including him in the magazine in one later issue was fantastic.
5:20
That that was that was unbelievable. >> I love it.
5:24
You know, it seems to me as I talk to people who have incredibly varied interests that that that seems to be part of the tale.
5:32
I also kind of grew up in a house that was just filled with books on very different subjects.
5:37
And you know, I would like any kid like I would pester my dad, why but why does this work? Why?
5:45
And he would just like I actually took it from him with my own kids.
5:49
He would just point to the bookshelf and he'd say, go look it up in there.
5:54
And and and what I found because he had very varied interests, one thing always led to another.
6:00
And by that I mean like if if I was one time when I was really bored, he brought me in to where he had all his books, his library, and he pointed at the Encyclopedia Bratannica.
6:12
I think it was vintage 1960 whatever.
6:15
Um and he said, "Read that."
6:19
And honestly, that was maybe the coolest thing that happened in when I was young because you can't help but be like, "Oh, wow.
6:28
I got to learn more about this now."
6:30
It's easier today, right?
6:30
Because I I'm I'm taking a stab at writing my first fiction book.
6:36
And honestly, I could not have done the research without large language models.
6:43
It it would have I would have I would have I would have needed a staff of historians, people uh you know uh versed in science and in technology and all of that.
6:55
And I I find one of their abilities that I use a lot is the ability to synthesize information from very different fields.
7:06
That was one of the reasons I was so excited to talk to you because that's what you you you that's your day job.
7:13
I would love it if that was my day job.
7:15
Like what are your thoughts on where we are right now?
7:18
Like we're kind of in media res, right?
7:20
Uh with with where things are going.
7:23
Um but you know, as I was getting ready, I Unix for example has been called the epic of Gilgamish for programmers because there's an oral tradition, right, where a hacker could probably re recreate it from scratch.
7:40
that isn't going to happen with large language models. Or am I wrong?
7:45
C do do the the scientists and innovators of today do do they have a tradition that keeps that knowledge building and going forward? I think so.
7:56
forward? I think so. Um I mean when when you look at how scientists and technologists do what they do um often times I think people think that if you just look at the scientific literature then you'll understand okay here is the
8:13
current state of the conversation around some scientific discovery or certain certain fields um or you'll kind of understand okay these people are working on this thing these other people are working on this other thing and and
8:22
that's definitely true I think looking at the literature you can actually understand that but the truth is um And my sense is that there's often a lot of like implicit knowledge in how scientists and technologists are doing what they're doing and where it and
8:36
because the truth is when you look at scientific papers and often times that's like several years out of date because they worked on it two years ago and it takes time for it to be for for it to be published. you have to really talk to
8:45
published. you have to really talk to the scientists and it's the kind of thing where really understanding what is happening in a scientific field or the kinds of techniques that really have the ability to kind of uh move forward and you're not going to learn that from
9:02
reading the papers you're going to learn it by talking to the scientists at a conference late at night at the bar like that's where you kind of learn the different things and so I think to that extent there definitely is a certain amount of this oral tradition and and a and sort of a community that passes things along. Um, and you'll you'll see
9:19
Um, and you'll you'll see this, it could be a situation where there might be like a materials and methods section in a paper and when you dig down into it and you actually talk to the scientist, they're like, "Oh yeah, really the only person who knows actually what's going on is like some postto who maybe was there several years ago."
9:34
Like there's the there's very much like there's like the keeper of the tradition um who might be still in the lab, who might not be.
9:39
And so there definitely is that kind of thing.
9:41
definitely is that kind of thing. And um and actually going back to what you were saying with um with these with language models and being able to synthesize knowledge um I definitely think one of the powerful aspects of them is the
9:55
ability to overcome jargon barriers because actually one of the things like when you are when you take one step outside of a field you don't even know the kinds of questions and even the words and terms to search for and language models help you overcome that. And so I I remember this this I think I
10:07
And so I I remember this this I think I tell the story in the halfife of facts but when I was when I was doing my own posttock me and another postto we were working on some research and we had a cluster data in some specific way and we needed some technique and we couldn't figure it out.
10:20
We did some searching like okay we'll make something up and we'll invent a technique.
10:23
It's not going to be very good but it'll be good enough.
10:25
And then we decided why don't we just before we do this like just talk to the statistitian down the hall.
10:29
And then I feel like within under 60 seconds he told us exactly what we needed.
10:33
And it was the thing we didn't even know what to search for.
10:36
And so language models really help with that overcoming jargon barriers and kind of collapsing things together so people are not constantly reinventing things.
10:44
For me, the downside sometimes though is is in the rapid synthesis and overcoming jargon barriers, you sometimes lose some of that serendipity.
10:52
So when you have to look at encyclopedia or dive into the stacks and find something, you also find a whole bunch of other things that you couldn't have anticipated and didn't expect.
11:01
And that can in turn lead you to other things.
11:03
And so for me, there's always kind of a there there's a trade-off there.
11:06
Yeah, I I think there's always trade-offs in every new innovation and the way we use it.
11:12
You know, McLuhan famously said, uh, we fashion our tools and then they fashion us.
11:19
Um, but one of the things the that you mentioned we're finding at Oshani Ventures is very true and that is the benefits of having a cognitively diverse team, right?
11:32
Like I think they got it wrong when when it was like DEI and and it was not about cognition.
11:42
It was about like what color is your hair?
11:45
Are you bald or are you you know not? Are you old or young? Are you black or white?
11:49
I I I think that those are the wrong ways to divide people and uh the the whole labeling.
11:58
Well, that that would get me on another rant.
12:00
Uh that that isn't going to be gerine here.
12:02
But listening to the story, going down the hall to the statistician, we find that when we get together in real life, right, all of those wonderful serendipities happen like at 10x when we're just doing async communication with one another.
12:23
with one another. So on the one hand like I'm all in favor because we you know the internet has basically collapsed geography, time and space right and you can be wherever and your colleague can be in um Mumbai and you
12:37
could still work together but now it's creeping in more and more right that a lot of these exchange as you say at the bar at night right h how would you optimize for that like what what kind of setup would you think would be close to ideal to be able to do both. >> Yeah. Oh, that's a good question. I >> Yeah.
12:58
Oh, that's a good question.
12:58
I mean, well, one thing I will say with um when in terms of like bringing people from different diverse kind of diverse domains and different fields, one of the interesting thing I think people studied this in relationship to patents when they found that people coming from different fields that it was um there was actually a higher it was not one of these things where on average they were always going to be better.
13:20
it was kind of they they actually had a higher variance.
13:23
So like when they succeeded, they succeeded much better than much better than would be expected, but then they also failed a lot.
13:27
And so there's kind of there's a certain art to figuring out the right way to kind of balance these things.
13:32
And I think that's kind of also what you're talking about.
13:34
How do we also balance the like bring people from lots of different areas, geographic areas, allowing people to work remotely, but also kind of in person.
13:41
Um, and for me, I mean, there's definitely a lot of research showing that that kind of in-person interaction really does have a certain amount of of of magic in terms of kind of these unexpected uh considerations and interactions and and this kind of magical information flow in a way that you would never otherwise expect.
13:59
Um, that being said, I mean, I've actually been remote for about for probably over a decade.
14:04
Um, so I uh and I definitely think there is something to be said for being able to actually be successful even in the absence of being in an office.
14:12
That being said, I when I go when I go to the Lux offices and I spend a lot of my time just talking with the other folks at Lux cuz I want to kind of like drink in as much serendipity and things like that as possible.
14:22
But I do think there I mean with whether or not you're in person or remote, you have to kind of cultivate that unexpectedness because I mean there's many situations where you're in person and everyone is in person and they're all just with their with their headphones on kind of just doing their thing sometimes interacting with each other even though they're a few feet away but entirely on on computer on the computer.
14:44
And so that obviously is not doing what it should be doing in terms of kind of those serendipitous and unexpected connections.
14:54
connections. And so I think there's a way of kind of crafting how the almost like the information diet that you get that is that feel that's kind of this combination of things that you need as well as things that are unexpected and
15:06
which in many ways uh and I'm kind of thinking on the fly and kind of spitballing but like in many ways that kind of parallels the way we think about innovation more broadly which is it anything that's new and creative is this kind of combination of things that have come before. So it's kind of this
15:21
So it's kind of this balance between expectedness and unexpectedness.
15:24
And I think that's and so in terms of that how innovation works, that's really what it is.
15:29
And so how do we think about doing the same kind of thing in how we in our in our work actually kind of balance the the expectedness of we just need the information flow to actually get our work done as well as kind of the unexpectedness.
15:43
And that I mean this is a very long way of saying I can kind of think about that problem.
15:47
I'm not really sure I have the answer, but I think uh I would say and maybe this is my just my sort of my bias towards working remote.
15:58
I think it can be done whether or not you're in person or not.
16:00
It really is just a matter of being very conscious of these kinds of things.
16:06
And so I when I have long conversations with people over Zoom or whatever it is, uh we can have lots of different directions, lots of different conversations.
16:15
And it doesn't really matter as much whether or not we're in person or not.
16:18
It's much more about making the space for undirected interaction.
16:26
And maybe that's what it is.
16:28
And so for me, >> I love just reaching out to interesting people and saying like, "Let's just chat."
16:32
And and I'll be very upfront like when we when we when we'll get on Zoom, I'll say, "I'm not really sure I actually have an agenda for this kind of thing.
16:40
I really just and I'm happy to tell you about kind of my own background.
16:42
Here's the things I'm thinking about."
16:43
And we just kind of go from there.
16:44
And then sometimes those are the most exciting conversations.
16:46
And so I think you can still do it whether or not you're in person or remote.
16:49
You have to just make that space and make it very explicit.
16:53
Let's have that undirected kind of exploration.
16:57
>> You know, that is kind of the conclusion that I'm coming through.
17:00
Everything is a work in progress, right?
17:02
Um but I I agree that unstructured is key.
17:06
In other words, you know, we often just get locked into an antiquated way of doing things.
17:16
What you mentioned what is the agenda, right?
17:19
like the I've learned probably some of the coolest things that I know now uh through unstructured uh conversations with people and and what we're trying to do right now to your point about the people being right next to each other but with the earbuds in and and you know texting each other on the computer.
17:39
We are going to be doing more in-person gatherings, but they are going to be explicitly unstructured.
17:46
You know, when we have we have an annual meeting of all our fellows and our teammates and everything.
17:54
And what we've learned uh this will be the third year we're doing it is the first year very structured.
18:03
The fellows all spoke individually about what they were working on.
18:09
You know, the teammates from the various verticals we have were just on that and it was great, but nothing like the second time around when we were like, you know what, why don't we just uh have this three-hour block of time where everyone's together and we just you can break into groups, you can do whatever you want.
18:28
And that works so well that, you know, the third year was even more of that.
18:33
and and the one we have coming up will have the same kind of a agendaless agenda.
18:38
Uh I know that's a weird way of putting it, but it really does seem to work.
18:44
Um I also want I I'm fascinated by this idea of, you know, kind of open-endedness in systems.
18:54
Uh systems that, you know, continuously produce interesting artifacts on their own, right, are open-ended.
18:59
evolution, civilization are your kind of arctypical ones.
19:05
Uh what what would indicate to you uh in the current ecosystem of say large language models that they've that they've truly crossed over into open-endedness.
19:23
So yeah, with open-endedness, I mean, I think the hallmarks are kind of this like like recombination in ways that you would not expect, which I mean also is related to kind of this unexpectedness.
19:36
There's kind of this like unexpected recombination that that feels to me sort of like the the open-endedness.
19:40
Um, and I guess maybe I mean really the hallmark of it is when you run these things for long enough, do you keep on getting new interesting things?
19:50
interesting things? Because I mean with with like a like like computational evolution or like evolutionary computation kind of models, these things are very sophisticated, but by and large um especially if you're optimizing for a
20:01
certain thing, you optimize for that and then they kind of stop after a certain amount of time and whether it's like genetic evolution or genetic programming or other kind of other kinds of techniques, they're not necessarily going to continue generating new things. You kind of generate a certain there
20:13
You kind of generate a certain there might be a certain burst or maybe it kind of plateaus and there's another burst, but eventually it kind of stops.
20:19
And so and and same thing with civilization.
20:22
We keep on getting new things.
20:24
We keep on getting new technologies and new ideas and that's amazing and that's what we want.
20:27
Um with language models, I think you would want the same kind of thing.
20:31
And I wonder if whether or not I mean the language models we have right now don't necessarily feel that open-ended to me.
20:40
Um and so maybe that's just a matter of taste.
20:41
But I also think maybe we just haven't run the experiment for long enough.
20:45
I feel like this is one of those kinds of things, especially when it comes like evolution in computers.
20:47
A lot of the times when we've done these kinds of experiments, we just don't run them that long relative to the the eons of true of like actual natural evolution.
21:00
And so we don't even know.
21:00
Um, obviously we have a good sense of why maybe these things have stopped, but when it comes to like language models interacting with humans or doing kinds of things.
21:07
Um, maybe we it they're still really new like and certainly whether it's on a civilizational scale, on a technological scale, on a biological scale, these things, they've been around for less than an eyeblink.
21:20
And so to say whether or not we really understand their true open-endedness, I I feel like we it I'm not really sure we know the answer yet.
21:30
And and so to kind of say either one is is premature.
21:35
Now, of course, and we keep on developing these kinds of things.
21:36
And this is also just related to the fact that I anytime you say, "Oh, humans can do this and humans can be open-ended or whatever and and these learned language models cannot."
21:44
Um, of course, like 10 minutes later, you find out that, oh, actually these things can do whatever the things we thought was only unique to humans.
21:49
And so we kind of have to have a certain amount of humility there.
21:51
But I think um when it comes to language models interacting with each other and and imagine also even just a civilization of large language models all interacting right now, we don't really have the computational capacity for doing for even running those kinds of experiments or maybe not necessarily running them at scale.
22:08
And so yeah, I I'm not really sure we know.
22:10
And and I think that's kind of exciting that it that we just haven't truly run that experiment yet and to to know whether or not they're entirely open-ended.
22:17
I imagine I there's many people I think who would say we have good reason to believe they're not quite there yet.
22:22
Um but I think it's exciting that there could be so many experiments we have yet to run.
22:29
>> I could not agree with you more.
22:29
Uh my friend David Ha who you might know his work um he he when he uh broke off to start his new company he he was basically just obsessed by the idea that nobody was doing evolutionary uh development of large language models.
22:48
And so I was talking to him once and like he explained the whole thing to me.
22:52
I understood maybe 40% of what he said to me.
22:54
But like I was really truly intrigued by that.
22:57
And then when I was getting ready to chat with you, your idea that we should study messy biological systems, uh, really struck me as a a good way to proceed in terms of having more of this development because I agree with you, we're probably not there yet.
23:19
And there's that great quote about it is really dangerous to understand new things too quickly because we probably have not understood them and it will lead us to very bad things by saying, "Oh yeah, I got that.
23:35
We this is the way those work and we can shut the case on that."
23:37
I I think that's one of the kind of bugs in human OS that, you know, we we I think we're far too quick to believe that we know everything.
23:52
And I I I have the opposite um suspicion.
23:55
I my suspicion is we you know to Edison's great quote, we don't know one one half of 1% of a millionth of things.
24:05
But like h how how do you structure work in that kind of environment?
24:10
How how do you guard against this sort of as I was getting ready I was I was going through the world three global system dynamic model developed at MIT which you've talked about in 1972 that led to the limits of growth and of course I thought instantly of Mus' on population paper from 1798 and he got the math of the population right if you if you looked at the the growth of population Malta's nailed it.
24:42
What he didn't nail, and I view this as a bug in human OS, he he thought that the ability to feed that population was fixed. Right. >> Right.
24:54
>> And and so he made the eminently linear and understandable argument, hey, we're we're going to hit a a zone where all we'll know is famine and death if we keep going at this level of population.
25:09
And he he he got sucked into what David Deutsch would be the would say was the hey you don't know what we haven't discovered yet right and you don't know that the hobbos process is going to double disposable nitrogen and be able to have the population go from 1 to 8 billion and counting.
25:30
And then and then I I was thinking about the world three thing and its narrative arcs, you know, business as usual versus stabilized world.
25:38
There there seems to be again the back test they did on that on what they projected found that they were right on population on industrial output, but they missed the the the big discontinuities that weren't expected, right?
25:53
That were kind of black swans like the energy shocks.
25:58
They didn't think that a cartel might say, "You know what?
26:01
We're we're gonna embargo the United States and cause an oil crisis."
26:06
They didn't anticipate the break up of the USSR and on and on. Right?
26:11
So, it's that part of the modeling that I find fascinating.
26:17
The the really how do you design a model?
26:20
Like if we if I asked you okay I'm like I want you to develop a model that takes this into account and takes you know uh what was Rumsfeld quote uh unknown like that known known unknown unknown.
26:35
Yeah right but I think that you know everyone makes fun of him for that but I there's a lot of insight there.
26:42
>> Absolutely right like the unknown unknowns are the ones that come and bite you in the ass.
26:47
How would you model for that? Yeah.
26:49
I mean I mean so when I think about I mean and there's some what is the quote of where it's like like all models are wrong but some are useful kind of thing like every model is going to be right. Yeah.
26:58
So every model is going to be a simplification of reality.
27:01
And the question becomes what do we what do we want it for?
27:03
Cuz sometimes we just purely want it for prediction.
27:05
Um so like with like weather modeling >> often times we just throw more and more complexity into these things and they actually work and and they've actually worked better and better over time.
27:15
we kind of have this intuitive sense, oh yeah, weather model, like weather prediction is not so great, it's actually been slowly but surely getting better quite quite a bit over the past several decades.
27:26
Um, but but when it comes to necessarily like certain ideas around like intuitive understanding, trying to put the entire weather model in your head is basically an exercise in futility.
27:39
There's no way you're going to understand that kind of thing.
27:40
And so that for for understanding, that's an entirely wrong approach.
27:43
And so for me, I think when I think about like world three and like limits to growth, their models were inherently simplifications and and they're actually very upfront about that.
27:52
Like they have like I think the world um in their model has um like it's completely mixed population.
27:58
So there's no like geographic distribution.
28:02
All like all of pollution is like condensed or like and certain chemistry is like condensed into a single single number.
28:08
All of technology is a single number whatever it's all it's fairly fairly simple.
28:12
The interesting thing is actually and even though I think there's a lot of people I think who kind of crap on the world three model um as it kind of moved forward in in in the future um it actually wasn't so bad relative to the way in which the world kind of the like the the shape of the world.
28:27
That being said though they kind of really wanted it to be a either a spur to action or or or some sort of mental model to better understand the world.
28:38
Now I think to a certain degree with their model they actually had and they had certain like there was a certain ideology around the model as well that they were kind of putting in but and all models are like that kind of thing.
28:46
And so for me it really comes back to like what are we what are we trying to get out of this kind of model.
28:51
So like for example um like Sim City Sim City is a vast oversimplification possibly entirely biased oversimplification of how cities operate.
29:00
That being said, um first of all, it uh actually got a lot of urban design like urban planners to get involved in that field.
29:07
So that so great success, but in addition, it also just teaches you about the inherent nonlinearity and unexpectedness of complex systems.
29:17
And I think even though the actual city stuff is entirely wrong, the fact that it can teach you about that like how certain choices will have big effects or small effects or unex unexpected consequences, how systems bite back, these are all the things that humans are really bad at having an intuition about.
29:32
And we just need more models about that.
29:34
And so Sim City was really really good for that kind of thing.
29:37
thing. Now, when it comes to really large complex systems that we want to just better understand and better model, for me, I view it as and actually going back to what you're talking about with evolution and biology, actually taking a
29:49
more biological approach to these kinds of systems and having a almost like tinkering iterative approach to modeling and and approaching these systems and and including actually technological systems that we ourselves have built. Um
29:59
Um because oftentimes when you look at I mean AI systems are just really complex technologies that we have built as as a society they rival the complexity and nonlinearity and weirdness of biological systems.
30:13
And so when it comes to biological systems yeah sometimes people are like they talk about biohacking and try to hack that's often based on sort of like a like an engineering mindset that really does not grapple with the true complexity of biology.
30:23
What the way biologists work is they try to understand a little bit of a system in its entirety or how different pieces work together and then slowly but surely build up a more complex and complete picture of the system.
30:37
And I think that's the kind of thing we need to do even when it comes to whether whether it's natural systems like sociotechnological systems of our own design.
30:45
We need that actually that more like almost like like a kind of like a naturalist of old where they're just kind of collecting different species trying to understand bits and pieces and slowly but surely building up complete picture.
30:57
That's the kind of mentality we actually need for understanding these large systems.
31:01
And so for example, one would be um even and in the same way that like naturals collected like insects and bugs, actually collecting bugs in this case like errors and glitches is actually a really good way of slowly but surely building a more complete picture of a system because often times the model we have in our minds.
31:17
minds. it does not actually map onto the the actual reality and but we only notice it when something goes wrong when there's kind of like this weird gap of like I what was it like last summer when um all the Microsoft systems across the planet went down and affected airlines
31:32
and like no one really realized that everything was interconnected until this kind of thing went wrong or um a much more trivial example and I'm pretty sure the experts actually knew what was going on but years ago I was living in Boston and in the Boston I was living in Brooklyn and there was I think a water
31:46
mane broke and then um they were and so they couldn't get water from like the main reservoir and so they had to get it from a backup backup reservoir and they couldn't guarantee the quality of the water for several days and so they um they issued some like boil water order um and it was for all of the different
32:01
like various municipalities of Boston so including Brooklyn where I was living except for Cambridge, Massachusetts which was surrounded by municipalities that actually did have to boil their water and it was not until that failure that I realized oh they actually get their water from a different source. Now, of course, the people working with
32:14
Now, of course, the people working with the system, I assume, were well aware of where water was coming from for from Cambridge, but I I didn't learn that kind of thing until something went wrong.
32:23
But often even the experts and like the people who built these systems don't learn about how the system actually operates until we have these kinds of failures.
32:31
And so for me I think I mean obviously failures and they're troublesome and worrying but they're all there's also a certain way in which they should be celebrated because they actually reveal something more about how the system operates and kind of and and hopefully can allow us to bridge that gap between how we think it works and how it actually does work. >> Yeah.
32:51
Um, I've long said that failures are portals of discovery and rather than uh get upset by them or um you know uh cast dispersions on the people who are overseeing the thing that failed.
33:06
overseeing the thing that failed. I I think it's quite the opposite like it it offers us a huge opportunity to learn and you know our our mantra here at my company is crawl walk run and when you're crawling like I have six grandchildren I'm very lucky and most of them were all here last week and and
33:28
like watching them go when they're first learning how to walk like it like what a cool thing to watch because you just start thinking about can Can you imagine if we tried to impose on my soon to be one or my one-year-old grandchild who's now walking, learning, he's cruising the furniture and everything. If if we took
33:48
If if we took like a modern corporate view and said, "No, you can't do it that way.
33:55
You can't do it that way. You can't do it."
33:56
You know, all of these prohibitions, we would never learn to walk because guess what?
33:59
When you're learning how to walk, you fall down all the time. >> Yeah.
34:05
And then it's in the falling down that the child is like, "Oh, okay.
34:08
If I do it that way, I I go boom."
34:11
And and and so my idea is you we literally can't know everything.
34:23
Never will, I don't think.
34:23
I mean, that's just my speculation.
34:25
I'd be willing to put a long bet on it, though.
34:29
Um, and uh, you know, my my heirs could uh win that bet a thousand years from now.
34:35
Have you read uh the book When We Cease to Understand the World? >> I have. Yeah. Yeah. It's fantastic.
34:42
>> As I was getting ready for you, I just kept going back to that book, right?
34:46
Because there's that section in there where Heisenberg is freaking out because he's like, and it's it's fictionally it's it's a book.
34:53
It's a work of fiction using actual people and what they discovered.
34:57
I think it's a really novel format.
34:59
Um, but like he's freaking out like I don't know how I came up with this and he's looking at his notebook, right?
35:07
And he goes, "But I think I now have a way to understand reality.
35:11
Not just understand reality, but to manipulate it at its most basic level."
35:18
And and then of course it goes into the qu consequences, right? Like what?
35:20
He gets vertigo and he thinks I should maybe just throw my notebook in the sea here.
35:31
Is there a way in your view for to to to I don't I don't even know how to phrase the question to to ring fence new discovery.
35:42
Should we sh can't sh can't sh can't sh can't sh can't sh can't sh can't sh can't sh can't sh can't sh can't we what's your view on as because we're getting into some pretty heavy stuff now.
35:50
Yeah, I mean it's a tough question because I I think in some cases I I assume you mean in terms of like when we discover new things, should we kind of like limit who knows about it or how we advance or like slow down certain technological advance.
36:06
Is that what you're kind of >> Yeah. Yeah.
36:07
No, not not not necessarily that.
36:09
I'm I tend to be more on the side of like I don't want a panopticon controlled by a few people.
36:15
I don't think that gets you to better knowledge at all because back to cognitive diversity, right?
36:24
>> Um in in fact, like I'm vehemently opposed to a panopticon controlled by you.
36:31
>> Um in fact, >> doesn't sound like good words to live. Yeah.
36:33
It does not sound like good world. >> Awful world.
36:34
I mean, you don't really need much imagination to see what living in that world looks like.
36:39
Um and and yet I'm I'm also not a Yeah, let her rip.
36:43
le let's just do crazy things and you know damn the consequences.
36:50
I'm I'm looking for kind of the middle path. >> Ah yeah. Oh yeah. Yeah.
36:54
I mean so the way I think I mean when people talk about progress or technological advancement I mean oftentimes the way I think about it I mean well one one thing I will say is as much as I love thinking about the future and kind of what the future holds and like we were talking about science fiction earlier and all these different kinds of things I know I'm not that great at prediction.
37:12
Um, like I can remember, um, I think it was when my first book came out, this is back in like 2012.
37:19
Uh, I was I was almost like relieved that the book was coming out then because I knew for certain that like right after like that was going to be one of the last books coming out in print.
37:27
Everything was going to be ebooks and like there was going to be, you know, print books.
37:30
And of course, I was wildly wrong.
37:31
And like I I can think of other examples where I I was like, "Oh yeah, this thing's going to be happening."
37:35
Never happened or happened on entirely different timeline.
37:38
And so for me, and I definitely want to have a certain sense of humility about predicting the future.
37:43
That being said, when I think about how people think about technological progress and advancements and new discoveries and things like that, it's not it shouldn't just be, oh, like these are kind of these forces that we're we're just being buffeted by and like you kind of you pour progress and technology on top of things and science moves forward.
38:00
It's it's an accumulation of choices of like, okay, what what are the things we're learning?
38:07
What are the kind of world like what are the the advances we're making?
38:10
And so for me it's much more about okay taking a step back and saying what is the world that I want to live in like what is the world that we should be living in and then let's work backwards to try to make that that much more likely.
38:20
And so for me, when I see advances happening, I'm I'm much more disappointed by not necessarily the speed or lack of speed, but more if people are thinking or not thinking about or in this case, I'm disappointed by sort of the lack of forethought about the like the consequences of these kinds of things.
38:41
Like if there's a lack of intentionality about the world that I want to live in and make that kind of thing a reality, that that feels feels very disappointing.
38:49
And so, and you see this often times when a new tech, like when there's kind of a new technology or kind of a new buzz word that everyone's talking about, whether crypto or AI or whatever, and people are just trying to do things for the sake of doing things.
39:01
And that's not all bad, but it's often a hallmark of just not really thinking about the world that you eventually want to live in.
39:10
And so for me, actually going back to the science fiction stuff, one of the reasons I love sci-fi is it can give me like a suite of options of like, okay, here are the different worlds that I might want to live in.
39:20
Like, do I want to live in the Star Trek Federation world?
39:22
Do I want to live in like Ian Banks's culture novels?
39:24
Do I want to live in some dystopian future, which I desperately do not want to live in?
39:29
And let's figure out what make those what makes those things more or less likely? And then try to do that.
39:32
And I think that's the kind of thing that I think about when people try to do scientific discoveries um or make technological advancements. >> Yeah.
39:42
Um again we are very sympotico there as well.
39:44
I I think that the way I look at it is I think almost everything is downstream of culture u and culture is made up of many disciplines etc etc but staying with science fiction for a bit right so I I have been a bit dismayed uh by later science fiction because it was all just so [ __ ] dystopic and like ah you And by the way, I I don't hate it all.
40:19
Like I I it's not science fiction, but it's a it's a contemplation that I think is beautiful.
40:26
Cormarmac McCarthy's The Road.
40:26
Um like really a downer, but beautiful.
40:30
And it's not talking about innovation.
40:33
It's talking about love, a father's love for his son and what what that will do.
40:37
But the the unintended consequences if you bake in like persistent pessimism into a society.
40:48
I can't remember the author of the quote or the quip, but it was like, I don't care who writes a country's laws if you let me write its songs and stories.
40:59
and and and basically uh we actually started a publishing company because we didn't want to have non we didn't want pessimism to win the day in all science fiction and we just have coming out August 1st a book called white mirror which is more optimistic look at whature >> well Neil Stevenson the science fiction
41:21
writer he actually did he I think in partnership with Arizon Arizona Arizona State University a number of years back they did a had a project called project hieroglyph which which was exactly that which saying, "Let's try to actually envision these positive visions of the future." Um, and they had a whole colle
41:32
Um, and they had a whole colle collection of short stories.
41:34
And they worked with scientists and engineers to kind of get everyone to be as as creative and imaginative as possible.
41:40
Um, I think one of the one of the I wouldn't say problems, but one of one of the complexities there is often times the the the most interesting stories are when things are going wrong or where there's tension.
41:52
And so you kind of have to and so so for example like Ian Banks's culture novels often times they don't happen in the culture where everyone is in this post scarcity society and everything is perfect.
42:00
It's often at the edges where they're interacting with other weirder civilizations.
42:05
And so that and so there's always that tension there.
42:07
But I definitely think we need more visions of right of what the world can be like when things go right. Yeah.
42:13
But temper it with a kind of what I would call a uh rational optimism, a realistic optimism. Yes.
42:23
Uh because it the future is not problem free. No future is right. >> Right.
42:30
And and people will still be people.
42:32
>> And and that was the thing.
42:32
But it's almost like you're looking at my notes over my shoulder because I I was going to say people I call it human OS.
42:39
I stole that from Brian Romelli. I love it.
42:43
the human operating system doesn't change very much and you know in my old life as an asset manager I I basically said that you know the only sustainable edge is to arbitrage human nature and continue to be able to do it right because markets change millisecond by millisecond human nature doesn't budge like millennia by millennia but am I wrong right like I I think about the b what I call the bugs of human OS Right. The illusion of control.
43:13
Um like everyone wants certainty which we never can have.
43:19
You know, we're probabilistic.
43:22
We we we live in a probabilistic universe, but many are deterministic thinkers.
43:27
And ouch, that's a mismatch.
43:31
And you know, hilarity or tragedy often ensue.
43:34
Do do you think that you could build a system where where you kind of make human behavior uh a constant?
43:41
And by that I mean like tribalism uh you know status hunting uh you know inherent biases you know all all that big mix.
43:55
They just like we have libraries filled with books of well uh designed reproducible studies that like yeah confirmation bias is a [ __ ] and it just keeps persisting illusion of control like the need for certainty like can we hold that do what do you think is that something you can hold content uh constant or are we ultimately going to see changes in basic big human nature.
44:26
Are we going to patch those bugs?
44:29
>> I I'm not sure if we're going to fully patch them.
44:30
I I think if you look at human history, I mean, it's not single direction.
44:34
Like there's not kind of like like the the wig view of history is not really correct.
44:38
That being said, there have been improvements like at the cultural level of and and it's and it's less about changing human nature entirely and more about kind of managing it.
44:50
And I think actually this goes back to some of what we were talking about earlier with like and the biological and kind of tinkering understanding.
44:55
I think it's this that kind of tinkering approach with human nature is probably the way to think about it where it's less about oh we're going to change people and they're not going to be subject to these biases or these cognitive quirks and more about how do we reduce the effects of those kinds of things and make them and either make them less worrisome uh or or simply just make people more aware of these kinds of things.
45:20
And so and and so when we look at like the tribalism and things like that, we have actually over um human history kind of expanded our sphere of concern um in terms of who we kind of view as part of um like part of us versus the other.
45:38
And so I think like Robert Wright talks about this kind of stuff I think in non-zero and he actually has a book um I think related to kind of like I forget exactly the title maybe something related to like the evolution of God but kind of also using this as like looking at the evolution of religion as a um a history of kind of uh expanding spheres of concern.
45:57
And so I think we have found ways of managing some of these kinds of things.
46:01
That being said, yeah, there are these invariants.
46:04
Like if you if you read like ancient wisdom literature, like whether it's stoicism or the book Ecclesiastes, like the ideas in there, they are still extremely relevant because we are we're still people.
46:16
And so, and actually I so I I have a lot of lists on my on my personal website where I kind of collect various different things.
46:24
And one of them is a uh a cannon of modern wisdom literature because there's kind of there's a lot of books that sort of rhyme with things around ecclesiastes but are kind of steeped in more kind of modern wisdom kind of approaches or more scientific approaches and things like that and and so and but at the same time they still often have the same messages of these books that are and these texts from thousands of years ago.
46:46
So I think we might be able to change things at the margins and we have a certain set of good ideas that allow us to kind of tame the downside of human nature.
46:57
Um so certainly I think a lot of the advances like around um what we've done for society of like since the enlightenment these have been unbelievable in terms of finding ways to allow people who are incredibly different to operate together and maximize human flourishing.
47:12
That's great and that that's that's the end goal.
47:14
Um, but we also have to recognize that and humans are humans and these things are always going to be to be relevant.
47:21
So for me, it's less about changing humans and yeah, maybe there's some genetic things we can do.
47:27
Um, at that point, I'm not really sure we are humans anymore if we're kind of changing some of these things.
47:32
For me, I I I kind of have this deeply sort of humanistic approach to the world.
47:36
We're like, I like being human.
47:38
I like contending with sort of the the weirdness and richness of humanity.
47:43
Um, but still trying to make me kind of the best version of myself.
47:46
I think if we change ourselves too much, we're not the best versions of ourselves.
47:51
We're some other version.
47:51
Um, which could be good, could be interesting.
47:54
Maybe that's an experiment worth running.
47:55
I'm kind of arguing against myself right now.
47:56
But I still feel deeply that humanity and yeah, for all of its and for all of its goodness and badness and all the weirdness of the human OS, there's something worth preserving, taming, but also really leaning into and and so yeah, I just want to kind of be more aware of that deeply h those deeply human features and and recognize them and rejoice in them, but also kind of make make us the best versions of those things. >> Yeah.
48:28
Uh I I I agree and um that that leads me right into um something you wrote uh where you where you said that Ada Palmer credits Francis Bacon with inventing the very idea of progress.
48:43
Uh and I find that interesting because when we decided to give these fellowships uh it w I was inspired by Francis Bacon uh and his story of you know the Atlantean journal where they send the scientists out to collect all the data and bring it back and uh and and then contrast it with the Judeaic tradition which is more linear time.
49:07
Um and and you mentioned Ecclesiastes.
49:13
Uh the you know the most famous line from that is there's nothing new under the sun.
49:17
Um and the uh the end of your essay you you uh say the the race is not always won by the swift.
49:26
And I smiled because I thought of the Damon Renan quote which is the race is not always won by the swift nor the battle by the strong.
49:33
But that's the way to bet.
49:40
So, let's let's talk about that a little bit because you mentioned just a moment ago these forgotten innovations like can can you give me some examples of some that you've stumbled across and like wow what if we resurrected this one what would like like the the modern view on that I'm fascinated by that because I like you think that you can gain a ton of wisdom by by reading ancient ancient
50:08
things like Heracitis was the first to basically be you know the the same man cannot stay step in the same river twice and he was pre Socrates right um so I definitely agree that you know that kind of lindy look at things that continue to persist over generation after generation but I'm I'm less wellinformed on abandoned innovations uh do you have some examples of some you've come up Yes. So abandoned
50:37
So abandoned innovations.
50:39
I mean so that I mean I'm not sure I know as many of those I mean one of the things I and related to what you're saying though I I think a lot about just technological history more broadly.
50:49
Um and actually one of the interesting things I see in the the tech world especially kind of in the Silicon Valley tech world is a is a certain amount of historical ignorance around technological advancements.
51:00
Um oftentimes like proudly ignorant uh which for me strikes me as very concerning.
51:05
concerning. Um because for me I think and there is there is something to be gained from like understanding this kind of path dependence and and seeing the like the reasons behind why certain things were invented discarded um sometimes rediscovered and so for me um this is not quite ancient technology but one of the things I think about and so
51:24
like in in my new book the magic of code I talk a lot about technological history and that's well I would say there's two aspects one is uh tech and tech technological advancement is changing so quickly right now that anything I write that's kind up to the minute will still be out of date almost instantly and so looking to history is is less likely to change. But also I think technological
51:42
But also I think technological history is deeply relevant for how we kind of think about the world because especially when it comes to computing a lot of the things that we think are new.
51:52
A lot of the the discussions we're having that we think are new or the advances that we're making, a lot of the time those ideas were almost they were around almost with like within like the inception of the modern digital computer.
52:06
Like people from like the moment people made digital computers, they were thinking around things around artificial intelligence and simulation and certain ideas around biology and artificial life.
52:14
Like these things are not new.
52:16
And so trying to understand what people were thinking about and then recast it with okay we might have some new ideas we might just have better computational power can we actually revisit those kinds of things and rediscover them.
52:28
rediscover them. So like for example like right now when we're talking about certain ideas around AI and unanticipated consequences or certain things around alignment or work and meaning these are not new topics and like you look at like Norbert Weiner the developer of cybernetics and he had there's this great um I think it's a collection of his uh like a modified
52:48
collection of some speeches he gave called God and Golem Incorporated and in it he talks about exactly all those topics and the thing is it wasn't even just like oh in this like weird esoteric area of cybernetics if you all look If you also look at like the 1960s, like the original Star Trek, there was an there was an episode called the ultimate computer that dealt with basically all of these issues. Like I I watched it
53:07
Like I I watched it somewhat recently and I was just blown away by how they anticipated the entire conversation that we're having that we're having now.
53:14
So these kinds of things like looking at the these kinds of questions and um both the questions we're having, the technologies that people have used, how people have engaged or interacted with technology.
53:25
I think these kinds of things really enrich how we think about history.
53:29
enrich how we think about history. Now when it comes to going back to your original question of like like innovations that we've forgotten certainly within computing in the early days there was a lot of really interesting discussion around not using
53:43
like not just viewing viewing computers as like fun like whisbang gadgets but viewing them more as like these are tools to help us like be better versions of ourselves, think better, educate our children and looking to how people thought about those kinds of things. I
53:56
thought about those kinds of things. I think is really really useful because not necessarily not necessarily the the algorithms are going to be exactly what we want to use but the um like the innovation as sort of like like the vibe that they were kind of giving off I think that's something that we need to reinvigorate and there are people who
54:14
are thinking about like like the future of programming and future of coding they they get it they're already like they talk a lot about kind of some of these earlier days but by and large I feel like in certain aspects of like the Silicon Valley world we've kind of forgotten that and actually it reminds Um there's uh the Did you ever watch the TV show Halton Cash Fire? Do you know Do you know this? >> Of course. Okay. It's amazing. And so, right.
54:35
And so, like I think in the very first episode um so like at that point, I think it's 1980.
54:39
Um one of the characters says like the computer is not the thing, it's the thing that gets you to the thing. Yeah.
54:46
>> And like and like that's the whole point of computing.
54:47
And we've kind of forgotten that.
54:48
And I feel like looking back to these earlier days of how they thought about computers as the thing that gets you to the thing and the way in which they built these things and like even just whether it's like looking at like old computer magazines of the the kinds of software people were playing with and things people were trying.
55:03
I just find that incredibly exciting and invigorating.
55:05
And so yeah, there's a lot there to be to to be discovered.
55:09
Um, and and for me it's almost like I I I kind of want I almost want there just to be awards or competitions for people to just like go searching in the stacks of old technologies and find weird things and like like the history of software things that people tried that we kind of abandoned for certain reasons and maybe should be re like re-examined.
55:26
Like I I I would love to see things like that. >> Yeah. Um me too.
55:30
And I I've always been really big on context, right?
55:35
If you don't have context, I think Cisero said something like if you don't know what happened before you were born, you will remain forever a child.
55:44
And and the contextfree in and you attributed to some in Silicon Valley, but it's not just Silicon Valley.
55:53
It's like kind of everywhere, right?
55:58
>> I had a long conversation with a writer who's a young a young uh person uh millennial, not not alpha.
56:05
uh or Zoomer, but but his primary worry was that the obsession and addiction to the new, right?
56:17
Social media, for example, um really limited and and really had an effect, a very bad effect on people willing to, for example, I love the series by Will and Ariel Durant, the story of civilization.
56:31
I don't know too many people.
56:33
I've got a young guy who works for me who's reading the entire however many volume uh uh set of it, but I I and maybe this is just me being a fddy duddy, but like there is so much in there that is relevant to today.
56:48
And to your point about like the, you know, they were talking about this years and years ago.
56:56
Um, we're developing an on-prem AI and so I was going kind of through the history of it and like the Economist magazine which was a very widely popular is a very widely popular they were writing about AI back in the late 80s and and 90s, right?
57:13
And I'm I'm reading this and and I'm like, this sounds like it could be written today because they were hand ringing.
57:21
Oh, is it going to, you know, they're going to take the job of the white collar uh workers because you don't need accountants anymore when it can be shrink wrapped and put on a shelf. Now, there's a problem.
57:32
They didn't anticipate that we wouldn't be going and buying software in stores again.
57:35
But I the idea of context, I I love that.
57:38
And I like maybe maybe what I was just thinking you you're aware of our fellowship program. Yeah. >> Yeah. >> Okay.
57:51
So would you be willing to work with me and we'll make a special fellowship for next year when we open them for 2026 to have get find a fellow you know fund the person not the project.
58:03
Uh where we find a fellow that literally does this task.
58:10
>> Oo this is interesting. That That's a fun idea. That's kind of wild. I love this idea. >> Yeah.
58:15
So, I mean, like I'm just thinking of this now.
58:17
Like, what a great idea I'm getting from you.
58:20
Like, if if you wouldn't mind giving us some input, like we could design what we're looking for and then go find that person.
58:29
>> Oh, that would be interesting. Oh, yeah. To find Yeah.
58:30
To find Yeah. to find the person who kind of and and you kind of want right you want someone who's knowledgeable maybe not too knowledgeable so they can be kind of excited by finding some of these new things and >> I definitely want a tinkerer and a
58:44
generalist not I I you know >> yeah there's definitely something there right to find yeah to because I think I mean >> and and the truth is even even if they find something that is not necessarily new where someone will be Oh yeah, like we we've known about this kind of topic for a while. There's something to be
59:02
There's something to be said for really and fundamentally like like the import export of ideas like that because because even if it's well known in this one little area, if they're not doing anything with it or they're not actually making it relevant to this other field, then it doesn't matter and right.
59:17
So you need this this process of like rediscovery or technological archaeology combined with this kind of import export process and making it actually relevant to the modern day. Um yeah.
59:28
Oh, that that that is super exciting. >> Cool. All right.
59:31
So, I'm gonna consider that a yes.
59:33
So, you're gonna be hearing from me later on as we gear up for the 2026 because I I just had that idea listening to you and like I love that idea. So, thank you. My pleasure.
59:49
>> Let's talk a little bit about humility.
59:51
And I I I have a friend who calls it prefall and postfall.
59:54
Um, and and you want to deal with postfall people, >> uh, because they've had the [ __ ] kicked out of them so many times by the world.
1:00:05
If they're still in the game, they have a certain level of humility that they did not have prefall.
1:00:10
I saw it happen in my own life, right?
1:00:13
Prefall, I was a proitizer and this is the way and I will tell you and I shall tell you all and then and I'm like, yeah, I I made a lot of mistakes.
1:00:24
And in fact, I I wrote a piece called Mistakes Were Made and Yes by Me.
1:00:29
Um because there's this kind of idea that is prevalent in not only investing but in business in general, in academia as well.
1:00:37
And and it's this this fear of like or this desire to, you know, always appear to be right.
1:00:47
And I just think that that's toxic, right?
1:00:49
Like I if I could get people to just utter one phrase more often and more sincerely, it would be to answer I don't know. Right?
1:01:02
And because that's the spring of curiosity.
1:01:05
That's what gets us like I when I would was in asset management, they would ask me a question.
1:01:11
I'd say, you know, I don't know, but I hope I can find out.
1:01:15
If I do find out, I will give you the answer.
1:01:17
Why is that just part of human OS, do you think? Yeah.
1:01:24
And I would have to say so.
1:01:24
Yeah. And I would have to say so. I mean it it and it's maybe a certain amount of like insecurity like wanting to kind of show that you know everything, but it's and or maybe maybe it's just maybe it's just not knowing how exciting it can be to actually not know things like cuz like for me I mean one of and you were you were mentioning about like running to the encyclopedia and looking things up and for me like like a family
1:01:54
dinner is like is a success when we have gone and looked into a book or like when my kids ask me a question I'll say I don't know and then we like go try to figure it out together that that's an unbelievable feeling and and and I think
1:02:08
that yeah maybe people don't necessarily just realize the true joy of that now of course the I don't know is somewhat different than the um like I was very certain of something and now I might be wrong. Um and so like for example there
1:02:20
wrong. Um and so like for example there was um uh and I think and that kind of thing to a certain degree it's almost like that is the it's ultimately a scientific mindset like like not like science in terms of like thinking about very specific scientific areas but like in terms of how science is actually done
1:02:37
and so I was reminded the um a professor of mine from graduate school he actually told me this story where he was um he was lecturing about some topic and I think he went in on Tuesday le lectured about some topic and then the next day he actually read a paper that invalidated everything he he had taught. And so he came in on a Thursday or
1:02:53
And so he came in on a Thursday or whenever it was next and he said, "Remember what I taught you? It's wrong."
1:02:57
And if that bothers you, you need to get out of get out of science.
1:03:00
And I think like that kind of idea that like things are constantly in a draft form that can be really rewarding and exciting, but it's it's very hard certainly outside of science and to be honest even in inside science if you are the one having your own discoveries being overturned.
1:03:16
A lot of scientists fight tooth and nail to avoid that kind of thing.
1:03:20
And so it's very easy to say in the abstract when it comes to so I think when it comes to knowledge overall and being overturned and being wrong and things like that scientists get that when it comes to their own science that's a whole different matter and and they're still very human going back to human that I science is being done by humans and so they're going to be very human when it comes to having things being being contradicted.
1:03:39
Um but yeah, so I I think we just need more of that kind of that kind of mindset where it's good to work at the frontier of knowledge where you know the least the most exciting things are happening but things are constantly being overturned. Like that's great.
1:03:58
Um to to be told that some bit of information you have in your mind is actually some it was it was just half remembered and and and you're actually wrong.
1:04:07
wrong. like that should be something worth like celebrating and saying oh now I get get to learn more about that kind of thing and then related to that is like the whole I don't know like you want to learn more things and so I think maybe it's a cultivating that kind of yeah the scientific mindset a certain
1:04:24
amount of curiosity as well as just recognizing that I mean we have clawed back a certain like a huge amount of ignorance about the world but there's still so much ignorance we have and that's fine like that that's okay I mean we've done really really well as as as a species, but there's still a lot left to learn. And uh yeah, it's that's just
1:04:40
And uh yeah, it's that's just fine.
1:04:44
Not only is it fine, it's great. >> Yeah.
1:04:46
Um one of the things that I started doing about 10 or 15 years ago was like I I started treating my beliefs and things I thought I knew as just uh hypothesis, right?
1:04:59
and and it helped enormously because one of the it it made it so much easier for me to say, you know, this model I had of, you know, topic A uh worked really well and then started to really disintegrate and it was when I went hunting as to why that happened.
1:05:21
Wow, there was all this new research as you say in your story uh that uh very persuasively um uh negated what I thought I knew and and by treating it like a thesis or a hypothesis, right?
1:05:37
I didn't attach it to me.
1:05:40
I didn't attach it to, you know, Jim and you know, it's like the people who say that hit, you know, if you go on social media, right?
1:05:48
Everyone's saying a hill all die on is right and and and I always joke that I take the general George S.
1:05:56
Patent approach that I'd much rather have the other poor dumb bastard die on his hill.
1:06:01
I'd rather change my mind and I'd rather delete an old belief that is no longer serving me.
1:06:07
And yet it's also that then now we come back to human OS, right?
1:06:13
the the desire for a coherent personality, right? A coherence.
1:06:22
People start freaking out in my opinion.
1:06:25
This is just me speculating.
1:06:25
I'm probably wrong, but like when when when they have to give up a cherished belief, something that they've invested themselves and their own sense of self into, it's like a mini death, right?
1:06:37
and they don't want to give it up because they're they're like I I'll decoher >> or people will think you know I'm flip-floppy or you know I'm I just uh don't have uh you know solid uh pillars to my various beliefs man all these pillars are built on sand in the f right like by that I mean you when you think that way you you it just makes it a lot easier to delete old beliefs, use the newer model.
1:07:15
It's just a an ongoing thing, right?
1:07:18
And and you know, you addressed this in the half-life of facts, like it's getting shorter.
1:07:23
It's like how do we were talking about textbooks the other day, right? I love physical books.
1:07:32
I love the artic the artifact of a physical book in my hand, but if we ever got into textbook uh publishing at Infinite Books, my point of view was they got to be electronic books because >> the the minute you yet the minute you print them, they're out of date and and like not useful.
1:07:54
>> What What do What are your thoughts? Yeah.
1:07:57
I mean I mean certainly when you're saying about um yeah just being able to yeah update things and kind of yeah delete these old beliefs and kind of change things and modify it.
1:08:07
I for me and I view like someone who is willing to say these are the things I tried or thought were correct. They were wrong.
1:08:17
For me that I those are the people I find much more appealing than the ones who kind of stick with their ideas or their ideas have never changed.
1:08:23
that doesn't that doesn't feel as interesting to me.
1:08:27
I'd much rather have people who have slowly but surely kind of like asmmpttoically approached the truth through updating things and changing things.
1:08:33
So yeah, when it comes to I mean yeah textbooks right they've obviously changed uh over time.
1:08:37
Um I definitely think looking at old textbooks, old print textbooks is is great as an artifact. Fascinating.
1:08:43
And actually and and >> and but but in terms of right like when you think about okay what what would I include in a textbook if it were had if it had to be in print uh and not change it would be much more about how to constantly learn rather than any sort of facts themselves.
1:09:01
Um which I mean fundamentally that's really what science is like science is a it's not a body of facts.
1:09:08
It's really just a rigorous means of quering the world.
1:09:09
of quering the world. And so right so then suddenly every textbook is just here's how to actually go out and learn new things and and test things um when it comes to right the actual knowledge right it's always going to be in flux um and sometime and by and large it's often the things that are newest those are the
1:09:26
things that are most subject to to change that being said there are times when things that we think are more fundamental can actually shift as well and so we were talking about my grandfather earlier and so um so he was a dentist and when he was in dental school he learned the wrong number of
1:09:40
human chromosomes and he learned 48 instead of 46 because it turned out there was like this period of I think like several decades where we had microscopes that were good enough to to see chromosomes but maybe not good enough to count them accurately and the wrong number just made it into the like basic knowledge and and I think just the
1:09:58
fact that like something like that which we kind of take for granted as something that should be certain that it could change means we yeah we really need to have a a great deal of humility around these kinds of things and so um and I I would say medicine is probably the best in terms of understanding these kinds of things. Um so like they'll have whether
1:10:14
things. Um so like they'll have whether it's like certain like certain ideas around like continuing medical education or um like online I don't know I don't know if they're textbooks but kind of tools where you can constantly find sort
1:10:26
of the most up-to-date knowledge um and they kind of recognize this like there and medical students are taught in medical school like I don't know a decent fraction of what you learn is going to be like out of date or wrong within a few years of graduation. Um I
1:10:35
Um I think my father told me some story.
1:10:37
So he he's a he's a retired dermatologist and he told me that I think he had an exam where it was like a multiple choice exam where the same exam was given where like the same there was one question same choices one year it was one choice that was correct and the next year it was a different choice but nothing about the actual test itself had changed.
1:10:55
It was just we learn new things about the world.
1:10:58
And so I I think medical like medicine gets it maybe a little bit more than other domains because things are changing so quickly and lives are on the line.
1:11:08
But I I definitely think that kind of approach should be exported to all fields of knowledge. >> Yeah.
1:11:14
Um the uh the I don't even know what to call him.
1:11:18
I guess I'll call him a philosopher.
1:11:20
Jed McKinnon uh says that the the people he most he finds most interesting are are those that uh whose choices and decisions cause real consequences and he's he he maintains they are closest to truth in reality because the the uh the cost of being wrong.
1:11:44
You bring up doctors is death in certain circumstances.
1:11:47
But then he brings in two others that I find very interesting.
1:11:52
So he's got doctors in there.
1:11:55
He specifically calls out emergency room doctors.
1:11:57
Um, and but then he's got special operators in the armed forces like the SEALs and Delta and those people and interestingly enough, traders, people who trade >> uh in financial markets because like one wrong trade and your 10year history of making a ton of money and everything and you become a dead player, right?
1:12:23
and one wrong move when you're on reconnaissance as a SEAL and your your your brothers who are serving with you die.
1:12:33
Uh and obviously doctors.
1:12:36
Um I how how do you how do you how would we transport that mentality over to far less um consequent careers or areas where the consequences of being wrong are are far less dire. >> Yeah.
1:12:56
Yeah, I mean when I think about those areas, I mean, there's obviously like accountability um in terms of like, okay, you do you make a wrong make a wrong choice or do do something wrong or that's out ofd um it can have very real consequences, but there's also this very clear feedback of like when you do thing like you you kind of learn based on the things that you do.
1:13:15
And I think when it comes to other domains that the accountability and feedback are far they're far more attenuated or or we have feedback but it's it's it's less related to the decisions or kind of the the knowledge that you have.
1:13:33
have. So for example, if you were let's say in kind of as a scientist or you're you're just working in the in the realm of research, if there are worse consequences for you for you like overturning or or kind of or or uh or being willing to kind of o
1:13:54
overturn something that you thought was correct like if you say this is what I thought was correct but now it's actually wrong or I made a mistake and if admission of m of a mistake is punished more than the mistake itself. I
1:14:05
I feel like that's like there's a big issue there.
1:14:09
Um and so I think we need to find ways of incentivizing right that like admission of mistake where we kind of like valorize people who say, "Oh, I thought it was this and now I and now I I changed my mind."
1:14:21
Um, and so I'm not exactly sure how to do that, but I think that like incentivizing the admission of mistakes, um, is going to be the the key aspect here cuz I think cuz otherwise people will fight tooth and nail for things that there are the things that they hold on to.
1:14:40
I mean, this is what is it the um like there's a maxim from like Max Plunk where it's like like science proceeds like one funeral at a time. Yeah.
1:14:48
And like people have have people have actually tested that and it sounds like it's not quite true.
1:14:52
But there does seem to but it feels correct in the sense that right like we only are moving forward not because people are changing their minds but because the people who are unwilling to change their minds finally die or leave the scene.
1:15:05
And so there are many instances where people do actually change their minds.
1:15:09
But I think we need to to praise that more and actually incentivize and valorize that kind of thing and say like these this is the hallmark of success where people have actually had certain long-held beliefs and now they've changed them or they're willing to admit a mistake thing like that's the kind of I I think that's the key in in making the shift. >> Yeah, I I agree.
1:15:30
uh and in my old business of asset management, one of the things that protocols that we put in place was I told all of our traders and all of our people who actually touched the portfolio, making a mistake or an error will not get you fired.
1:15:46
Trying to cover it up and not telling us about it will get you fired every single time.
1:15:51
So basically my goal obviously was that those things be brought to our attention immediately so that we can fix them.
1:16:01
that we can fix them. And it was really interesting the a young trader came in after we kind of had that meeting and he's like that just that simple thing just makes me feel so much better because you know it's that kind of human nature and and I'm thinking we're talking about science and one funeral at a time and all that but back to human OS right uh you know the story of David Bow when he published his hidden variables
1:16:30
paper and Oenheimer uh who had been his mentor was told by the US government that guy's a red he's a communist I I we don't want him rising in the hierarchy and so there's records of Oppenheimer going to his colleagues and and basically saying if we can't disprove David we must ignore him and I I wrote a little piece on it basically saying yeah it's the plot for the movie Mean Girls right like you can't sit with us anymore David. >> Oh yeah. >> Oh yeah.
1:17:05
>> But but you know the kind of the whole idea behind the citadel of science and protecting their turf, right?
1:17:09
You get into these turf wars.
1:17:12
It's it's like the the fact that much of science is still clinging on to materialism.
1:17:17
I I just kind of find baffling given all of the the things that have been discovered etc.
1:17:27
uh that would say they might want to at least like change their thinking on some of those things.
1:17:32
But but also the the unwillingness to like if if you're applying for a research grant, it's highly unlikely that you are either going to write your grant saying we think that the uh hypothesis will be a null set, right?
1:17:51
It it it basically the the funders wherever they are in the government or private they don't want to hear that to the point where we we are thinking of when uh when we can get around to it.
1:18:06
We've got a a pretty large list of things we're trying to accomplish.
1:18:11
we're trying to accomplish. Like how cool would it be to have an AI just publish null sets just literally run through a ton of experiments and then publish them to a public database right because like learning via negativia if you're a mystery fan Sherlock Holmes
1:18:30
hounds of Baskerville right how did he know about who it was the dog didn't bark and he didn't bark because he knew the person right and and yet like I when when I'll speculate on this like the idea of publishing these huge uh uh data sets of null sets people kind of look at me strangely. What do you think of that
1:18:51
What do you think of that idea?
1:18:52
I mean so I know there's been at least been at least one scientific journal that I think tried to do that like published the like a journal of negative results or whatever it was and I don't actually know how successful it was.
1:19:04
was. my sense is probably not that successful because right now we incentivize certain kinds of things in science and I mean the way I kind of view science is like there's there's all the activities that are valuable for science and then there's like the subset of things that get you tenure like the things that are kind of valued by
1:19:20
scientific academia and we need more ways of valuing these other kinds of things whether it's I doing kind of weird interdicciplinary work or just helping other people without necessarily publishing your own papers or publishing negative results or doing research that maybe has like very high variance in terms of its outcome. Like we there's a
1:19:37
Like we there's a decent chance it'll it'll not succeed.
1:19:42
There's all these things um that that move science forward, but we often don't necessarily know how to to incentivize them.
1:19:51
And so there was there was actually this paper this is a number of years ago now where they looked at um I think it was in the field of immunology.
1:19:58
They looked like I think like 50 years of research or whatever it was and said um like who are the who are the researchers that were kind of the most highly cited but then they also looked at the researchers who were acknowledged
1:20:09
at the end of papers and they found and they they found that there was this group of scientists that were kind of they had like a mediocre number of citations but they were actually very highly highly acknowledged at the end of papers. And when those people died, the
1:20:19
And when those people died, the productivity of everyone around them dropped.
1:20:23
And so it showed that these people were actually really important for science.
1:20:26
And so they were doing something that was really important, whether it's giving out ideas or just kind of being helpful.
1:20:30
And and and I don't think the solution is to suddenly say, "Oh, now the number of times you're in an acknowledgement at the end of a paper counts towards tenure because I think then that'll be gamed."
1:20:38
But we just need to recognize there's so many more activities for moving kind of the endeavor of knowledge growth forward.
1:20:45
Um and including yeah exactly what you're saying like these negative results like finding all the ways that we don't that things don't work because often times right when when a lab runs an experiment it doesn't doesn't succeed throw it in a drawer and kind of move on and then other people do the same thing and they they recapitulate it.
1:21:05
So there's a huge amount of of duplicated energy and effort towards these things that we know don't work, but they're not kind of in the in the public record.
1:21:14
And so we yeah, we need so many more ways of incentivizing publication of negative results or helping or all these other activities that will actually move science and just knowledge forward. >> Yeah.
1:21:27
Um, and that as I was listening to you, I I was thinking uh about your view on, you know, things have become so intricate and complex that they're getting harder and harder for we humans to truly understand.
1:21:46
Um, and like if key infrastructure is genuinely beyond human comprehension, like what do we do?
1:21:53
I mean, I I know that's kind of a loaded question, but you're the right guy to ask it.
1:22:01
I mean, like, how how could how do we do reliable stewardship in practice if this is if this is correct?
1:22:10
So, I I think part of it comes down to just having a certain amount of awareness of the world that we're in.
1:22:17
And I I think and so the computer scientist Danny Hillis, he's written about how uh we've moved from the enlightenment when we kind of apply our rationality to understand the world around us.
1:22:25
Uh to the entanglement where everything's so hopelessly interconnected, we can no longer fully understand it.
1:22:29
And and that's clearly the world that we're living in.
1:22:32
But for many people, we we remain in ignorance in some willful ignorance of this kind of thing.
1:22:39
And so there uh a number of years ago when the when the Apple uh the Apple Watch first came out, there was this great uh quote I found in it was a Wall Street Journal article, I think it was like the style section about um about whether or not people are still going to wear mechanical watches.
1:22:53
And and of course people are still going to wear mechanical watches, but this this one guy was like, "Oh yeah, of course I want to wear a mechanical watch."
1:23:00
I think of like how sophisticated and intricate it is as opposed to a smartwatch which is just a chip.
1:23:04
And of course, like just a chip, like these things are orders of magnitude more complex, but we've been shielded from it.
1:23:10
And I think that's partly the problem.
1:23:12
And so when we think and because we're shielded from it and we don't necessarily think about these kinds of things when things go wrong or when we're confronted by these these kinds of complex and and over complicated situations where we don't fully understand them and things are going wrong and we have cascading failures, we're going to be blindsided and we're going to be really really distraught.
1:23:32
And so for me when I kind of think about the right way of approaching these technologies um it's somewhere in between.
1:23:41
There's kind of two extremes like when you look at like technologies and systems we can't fully understand.
1:23:45
there's either like um kind of awe in the face of these things of like oh my god like these AI systems are are beautiful or kind of the mind of God or like abject fear like oh my god like self-driving cars are going to kill us or AI is going to kill us and and some and having a certain amount like I maybe having a certain amount of concern is
1:24:04
useful but if you have both of these if you have one or two of these extremes the problem with either of these extremes is going back to what I was saying in terms of not being aware of how these systems work they also cut off questioning If you think these systems are amazing, you're never going to learn from them. And if you think these things
1:24:17
And if you think these things are fearful, you're going to be so blindsided by that fear, you can't you can't interact with them productively.
1:24:24
And so going back to humility, humility is really the proper way to think about this, which is to say, okay, we might never fully understand these systems.
1:24:33
But there is a great deal of understanding between complete and total understanding and complete and ut and utter ignorance. And we can work there.
1:24:41
And I and we can actually slowly but surely try to understand these things whether or not it's through biological thinking or kind of iterative tinkering or slowly but surely understanding different bits and pieces of a system and gaining a kind of like humble iterative approach to understanding the world.
1:24:57
Um I think that's the kind of approach that we needed and actually in going back to in terms of like um like historical wisdom uh so the uh so prior to the enlightenment um there was this understanding that we could never that we might not actually fully understand things completely.
1:25:13
things completely. So if you look at so the the philosopher physician and rabbi Moses Mymones in one of his books the god of the perplexed he he talk he actually he talks about how there are things we will never fully understand and they're kind of only in the mind of
1:25:24
god or whatever it is and he actually he actually gives a list um which is actually kind of interesting because I think one of them is like the number of stars in the sky and actually we actually do know the number of stars visible to the naked eye we actually
1:25:34
know that um I think he's like whether or not it's going to be the number is going to be ethan or odd I think we actually know it's even I don't remember exactly don't hold me to that that being said there was this understanding that there were things that we might never
1:25:45
fully grasp and and and I don't necessarily want to say that therefore just because there are things we might never fully grasp that therefore we should not try to continue to understand the world and understand the systems that are around us that we ourselves have built. We should definitely do
1:25:57
We should definitely do that.
1:25:58
But if we bump up against situations where we might not fully understand them, that's okay.
1:26:03
And I think having that productive humility is really the path forward in terms of thinking about these kinds of things. Yeah.
1:26:12
And that brings me back to as I was listening to you um human OS again, right?
1:26:18
Like this deterministic pattern.
1:26:21
Yes, no, 0, 100, black, white, right?
1:26:25
And I guess we can blame Aristotle for that because uh you know he he influenced quite a few number of of thinkers. But like that's wrong.
1:26:33
It's it that is not the way the world works at all.
1:26:39
It's it's like I I to me it just seems kind of the height of arrogance and kind of being stupid to think that we could truly 100% understand like anything and and and likewise like zero understanding.
1:27:00
I guess there might be something there, but it's always a continuum, isn't it?
1:27:04
continuum, isn't it? and and >> it >> no it's it's always there and it's also and I think one of the other things is like not only should we right have that understanding that it's a continuum of understanding but there's something to be said for even if we think we understand something preserving a little bit of that doubt or recognizing that um
1:27:28
we might be wrong or there are other ways of understanding the world and actually so um and there's the whole idea of like oh history is written by the winners or whatever so So if you look at like the ancient Talmud, one of the interesting things about it is it actually preserves the debates and the opinions of the ones that lost the ones we don't include like th that is actually part of the discussion. And I
1:27:46
And I think having that kind of intellectual humility of okay, we might be wrong.
1:27:52
Here's a number of other different opinions.
1:27:53
Here's how people arrived at these kinds of things.
1:27:55
When we think about science, I mean obviously science we preserve a lot of this knowledge, but often times we don't necessarily think about all of these like other paths not taken.
1:28:04
And this actually goes back to like this historical sense which is really understanding how we got to where we are.
1:28:10
What are the things that people tried?
1:28:11
How do we think about these things that I think also can help illuminate how to better understand the world around us?
1:28:18
We're never going to fully get there, but we like we sure as hell keep must keep on trying.
1:28:22
And like and the more we have on which to to grow and like as long as we have that context and that foundation, I think we'll be better positioned to actually understand that. >> Yeah.
1:28:33
And and and the challenge there is how how how do we build a system of incentives for people in and you know choose your discipline?
1:28:47
It doesn't have to be just science.
1:28:49
science. It doesn't have to be business like but how do we build a system of incentives that that reinforces that as opposed to frankly I think we're still operating under the old system of you were wrong you know that's going to cost you and uh you're fired
1:29:10
and you know one of the things that we did with stock market and investment research is we kept an invest what we called an investment graveyard yard which were was all of the ideas we tried and thought would work that didn't work because again you can really learn a lot from that. I'm just curious as to how
1:29:27
I'm just curious as to how would you how would you kind of design that you know and and I'm looking down at my notes and and and and like in in the magic of code you frame programming as modern sorcery.
1:29:42
I love that and prompting is spellcasting. I love love love.
1:29:46
And so can we cast some spells?
1:29:50
Can can can we can we uh uh do sorcery to get people in Senate to start thinking this way? >> Yeah.
1:30:01
I mean, so at least in the scientific realm, I mean, I was mentioning before like how like there's like the space of things that are relevant for science, like valuable for moving science forward and then like there's only the small number of things that academia actually like incentivizes.
1:30:12
Um, one of the things I've been actually thinking about is uh what are kind of new types of scientific organizational structures that we need.
1:30:21
And so when I think about the space of organizational structures and science and like in terms of things that allow you to do research and it's great that we have universities and corporate industry labs and sometimes even startups that are doing some fundamental research, but those are just like three points in some weird highdimensional space of potential institutions and we actually need to examine this entire space.
1:30:39
space. And so um and luckily I over the past I'm 3 five years or so um there's actually been a lot of really interesting innovation here and people have tried to make new new structures and new types of organizations that are more interdiciplinary they they fun people versus projects sometimes they're
1:30:54
funding just projects sometimes they're distributed sometimes they're doing weird kind of other kinds of things um but to be honest I mean I I'm I'm kind of agnostic as to which is the at least within the scientific realm like which is the one that's going to win out in terms of the the structure. I because I
1:31:10
I because I and people always talk about this is like there's a Cambrian explosion of a new type types of scientific institutions.
1:31:15
The flip side of any sort of Cambrian explosion in the evolutionary biology realm is there's going to be a probably big pretty big extinction event.
1:31:22
And so a lot of these will not they will not survive.
1:31:24
And and that is unfortunate for these institutions.
1:31:28
But that is the kind of the process of learning.
1:31:30
And so I actually think and to be honest I don't really have the answer of like what is the way to incentivize these kinds of things.
1:31:36
things. I just want there to be more types of institutions or organizations where people are able to do more different kinds of things whether it's doing weirder kinds of science um other kinds of places where they can admit
1:31:52
mistakes and failure or other kinds like and yeah maybe some of these won't win out but presumably another type of institution that has this kind of healthier this healthier relationship to knowledge seeeking or whatever it is will be quite successful. And so for me, I just want thousand
1:32:08
And so for me, I just want thousand flowers to bloom, million flowers to bloom, whatever it is, because we're going to eventually hit up hit upon new points in this highdimensional space.
1:32:17
And so, um, yeah, I don't know.
1:32:17
I just want more people to try things and experiment. >> Yeah.
1:32:21
And, uh, we I I completely share that point of view.
1:32:24
Um, you you you you can't tell until you just try a bunch of different things.
1:32:32
different things. And you've just got to be get yourself and your team uh really comfortable with the idea that like high extinction rate if if we're having a Cambrian like explosion you know uh a lot of these things are going to go extinct and that's okay right you in in my view it's like you having this no we are going to achieve X right and whatever X happens to And it's out here and this is the path that we
1:33:07
are going to no do not prescribe a single path that you are going to take there because you you have overindexed on one thing and your your likelihood of failure is just soarses >> right the going at it from like a thousand flowers blooming that you're
1:33:27
going to be much more successful >> and I think this is one of the things that Silicon Valley has done really Well, as a as like in terms of its culture is normalizing that kind of failure. Like you make a startup, it
1:33:37
Like you make a startup, it fails, you move on.
1:33:39
Like there it's not it's not a scarlet letter or you're you're not punished for all time.
1:33:44
You learn from it and then you take that experience to actually do something better the next time.
1:33:49
And and so I think maybe aspects of that culture and that kind of that kind of thinking to the broader society could actually be valuable. >> Yeah.
1:33:58
And the basically some of the some of the things that I've been able to accomplish came out of a big failure, right?
1:34:06
Like I I oh I think we should do it this way and it's just like woo mayday mayday as I'm bringing the plane into the drink.
1:34:20
But the the what you learn from those failures really really help.
1:34:29
And I I just I'm perplexed by what seems to be the majority view of really being frightened to embrace that kind of approach to the world.
1:34:40
Again, not just in science, but kind more broadly. >> Yeah.
1:34:46
And and maybe part of it is also just our current cultural moment where our identity is so tightly wrapped up in our professional success.
1:34:56
M >> and if if you have that and also all of your friends and your everyone you interact with is also in that world not necessarily even just in the same world of like wrapped up in professional success but really the same industry that you are in that when you have a failure it can really shake your entire community and like like your entire kind of like social network like in terms of like how you interact with everyone else.
1:35:23
If though work is work and it can be meaningful and can be fulfilling and it should be, but you also have like a broader group of friends and family that really are just entirely like orthogonally connected to all the different things you're doing about and if you try some things and you succeed or you try things and you fail and they don't care either way, that actually I think is really grounding and probably a lot healthier.
1:35:49
And so maybe that's what it is where we just need a a diversity of social networks so that like when you if you have a close group of friends who really don't care about what you're doing professionally then it makes it a lot easier to try things and fail or even succeed.
1:36:04
We're like they don't care about any of your successes.
1:36:06
That also is very grounding too cuz they're cuz you're the same person no matter what.
1:36:10
And so so maybe that's what we need just kind of in terms of how we think about our social our relationship to work as well as and I think the way in which we do that possibly is having that healthier relationship through having our social context context be kind of different and like orthogonal to to our work and our profession.
1:36:31
Yeah, I think that there's a lot of promise in that and it's we we have uh intentionally been building teams at Oshanas Ventures with that in mind.
1:36:42
We want we want people who um are are really really bright but really really uh not only humble uh but um fascinated by the interconnection between things.
1:36:56
And those kinds of conversations get to be like really interesting.
1:37:01
We had one instance where we had a fellow who is a scientist trying to develop a very particular um way to analyze poop essentially.
1:37:14
And um she uh spent an hour and a half with my editor in chief at Infinite Books, Jimmy Sony.
1:37:20
She came over to me afterwards and she goes, "Um, that was maybe the best hour and a half that I've ever experienced in my life because he had me explain what I was doing to him and then he outlined a way that I could market it or raise money for it that I never ever thought about, right?"
1:37:38
And and and I'm like, "Really?
1:37:41
Get, you know, tell me more."
1:37:43
And he I didn't even think of this quantified self Jimmy was bringing up.
1:37:48
I didn't even think that that type of person might be really interested in something like this.
1:37:53
And she goes, "So yeah, I've completely rewritten uh the deck thanks to my interaction with him.
1:38:00
Uh so I definitely have seen value coming out of it uh more than once.
1:38:05
So right now, Sam, what what is obsessing you?
1:38:08
What what are you just like, ah, this is so cool?"
1:38:11
So I mean I mean certainly I I'm thinking about I mean given the magic of code just kind of came out.
1:38:20
So I'm thinking a lot about that but for me I mean I've actually been thinking a lot kind of broader than that which is kind of around and so the magic of code it's thinking about kind of computing is like not just a branch of engineering but kind of this humanistic liberal art that like connects to language and philosophy and biology and art all these different kinds of things.
1:38:37
Um, but I've been thinking about what would it mean to take this sort of like humanistic computing approach and and take it really seriously almost like within our education like whether do we need new types of curricula or courses or or ways of thinking about this kind of thing and and and to be honest I I'm still trying to figure out what that means.
1:38:59
Um, right now I and going back to my obsession with list making, I have this like long list of like books and articles that for me kind of evoke that right aesthetic of these kinds of things that are kind of at this weird this weird intersection.
1:39:14
Um, then I've actually begun collecting courses that I found online that have like interesting syllabi that that I think also evoke that same kind of sense and I want there just to be more of that.
1:39:24
Um, I don't know if that's going to be a new field.
1:39:26
I don't I I would not presume it's a new field, but I think there's something there in terms of thinking about that kind of thing. Um, so that's one area.
1:39:33
Another topic that it's not it's not quite top of mind, but it's something that's like been just like itching in the back of my mind for at this point probably years, which is um so I mentioned earlier Sim City.
1:39:44
So Sim City was made by the by the company uh Maxis.
1:39:48
It was made by So Will Wright, he made developed this company Maxis.
1:39:51
They made Sim City and Sim Earth uh The Sims.
1:39:54
Um, and the heyday of Maxis was kind of like early early to mid 90s.
1:39:58
Um, and it was this weird moment when Maxis could be a game company that also was playing in the realm of like complexity science and other weird sciences, but also building these strange things that were not actually games, but were kind of just toys that were teaching people how to understand all these different models about the world.
1:40:18
And so, and I've been and I write about this periodically and I'm talking to people about what would it mean and is it even possible for there for there to be a Maxis 2. 0?
1:40:27
Like, could there be another company like that that built these I sim new simulation toys or was the bridge between the gaming world and various scientific domains or or kind of other esoteric fields?
1:40:41
Um, or what and was it maybe just this weird moment in time in the '90s that allowed this kind of thing to happen?
1:40:47
I don't think that's true.
1:40:47
I think there might be a possibility for a Maxis 2. 0.
1:40:50
Um, I've been talking to a lot of people in the gaming industry and other areas um to see just if this could even be a thing.
1:40:56
Um, and I have no idea what it would look like, but I've just I I just constantly return to this idea of Maxis 2.
1:41:04
0 as kind of this like placeholder in my mind for something that I kind of want to exist in the world. >> Yeah, me too.
1:41:11
Because uh what I love about that is games are fun.
1:41:14
And when you know my kids were growing up, they're all adults now, but my daughter was absolutely, you know, just completely infatuated with Sim City.
1:41:26
And like she would play that for hours.
1:41:30
And so like at dinner, I'd say, "Well, what did you learn about it?"
1:41:34
And I got to tell you, like it it she became this font of wisdom about things like, "Huh, I never thought about it that way."
1:41:43
And the the idea that you you can learn while having fun.
1:41:48
Ju it just seems so self-evident to me.
1:41:52
And and in fact, I I I I would love a 2.
1:41:54
and in fact, I I I I would love a 2.0 0 version of that because you know the who who knows given today's tools right who who knows what kind of uh things we could come up with by you know just tinkering just playing >> yeah like yeah could you and right
1:42:15
nowadays could you just kind of build your own sim city but with what whatever rules you want and and like yeah there could be so many interesting thing and and certainly with like the computational power we have at our at our disposal you could just build unbelievable weird playful simulations. Um, but I also Yeah, the the kind of
1:42:31
Um, but I also Yeah, the the kind of blending of education and gameplay.
1:42:33
I mean, one of the and with the original Sim City, I remember the manual, it had essays in it and it also had a bibliography and I poured over those essays and I read the bibliography.
1:42:43
I I convinced my mom to take me to the local university library and find some books there.
1:42:49
It was amazing and I I Yeah, it was fantastic.
1:42:52
Well, Sam, uh, I I know that I've been having a delightful and fun conversation when an hour and 45 minutes goes by and my producers start buzzing my cell phone saying, "Hey, Jim, this has been really fantastic.
1:43:07
Um, I I I love chatting about things like uh this with people as well informed as you."
1:43:18
Um, our our final question here is kind of a fun one, at least for me, and and that is uh we're we're going to make you the emperor of the world for one day.
1:43:29
You can't kill anyone and you can't put anyone in a re-education camp, but what you can do is we're going to hand you a magical microphone and you can say two things into it that will incept the entire population of the world.
1:43:42
Whenever their next morning is when they wake up, they're going to think of the two things that you incepted in them and they're going to say, you know what, inspirational inspiration is really perishable.
1:43:55
And unlike all the other times I had the great idea, I'm going to actually act on these two things.
1:44:00
What two things would you incept in the world to to make it one that that you you wanted to live in? >> Yeah.
1:44:10
So I I think the first one is probably not going to be that surprising.
1:44:13
Uh it's going to be you might be wrong.
1:44:16
And going back to kind of the ideas like intellectual humility, I think we just need that idea much more in our society.
1:44:22
Um so I would definitely say that.
1:44:25
>> The second one >> maybe use libraries more.
1:44:27
I mean, I grew up in libraries and like public libraries were like that's where I I learned so many different things and so many and so many ideas and exposed to like all these different books and it was just they're amazing and and I feel like not many people use libraries as much anymore and I just want more people to yeah to be used in libraries more. So use libraries more.
1:44:52
That would be my second one.
1:44:54
You you just incepted me because I like you loved libraries and went to them all the time when I moved to New York.
1:45:00
One of my happiest moments was walking into the New York Public Library.
1:45:04
Um and I haven't been using libraries nearly as much.
1:45:08
So I'm going to take you have incepted me. Awesome. Yeah. Yeah.
1:45:12
And and since when I was actually when I was very little, um my father knew the best way like to to get a hold of um to get a hold of my of my mom.
1:45:24
He would call the library and say he wouldn't ask for her name.
1:45:26
He would just say, "Can Sam's mom please come to to the phone?"
1:45:30
Cuz I was known cuz I was there all the time.
1:45:32
I was like this like 2-year-old or whatever it was.
1:45:34
And yeah, so I grew up in libraries.
1:45:35
I still try to walk to the library almost every single day.
1:45:39
Yeah, we we just we need to use libraries more. So, >> I love it. I love it.
1:45:44
>> Sam, thank you so much.
1:45:44
This has been so much fun.
1:45:47
Um, people can find you on social media.
1:45:50
I know you're on Twitter and all the other ones and they get your book everywhere. >> Yeah, you can. Yeah.
1:45:56
Get Yeah, get all my books everywhere. Yeah.
1:45:57
Newest one, The Magic Code.
1:45:58
I actually don't really use social media that much anymore.
1:46:00
Um, but uh um yeah, if you go on arbisman.
1:46:03
net, so just my last name. net, that's my website.
1:46:06
It has links to um my newsletter.
1:46:08
I do I do a podcast with Lux as well and all the other weird writing things that I do.
1:46:12
So I'm easily findable online. >> Perfect. Terrific.
1:46:15
Sam, this has been a joy.
1:46:17
Thanks for giving me the time. >> Oh, thank you. This is fantastic. >> Cheers.