← New Books Network
New Books Network
César A. Hidalgo, "The Infinite Alphabet: And the Laws of Knowledge" (Allen Lane, 2026)
01:06:35
Loading summary
Transcript53 lines
- [00:01]
Timberland Narrator
It's not just something you made, it's the privilege that you get to work with your hands. It's building something that serves a purpose, proof that you have the grit to keep going. At Timberland, we understand you take your craft seriously, and we do too, which is why our products are built to the highest quality. We put in the work so you can perfect yours with purpose, in every detail, and crafted with intention. Timberland Built on craft. Visit timberland.com to shop.
- [00:32]
Focus Features Announcer
This episode is brought to you by focus features on March 27, Focus Features invites you to be a part of the most explosive movie of this year's Sundance and South by Southwest film festivals. The AI Doc or How I Became an Apocalyptimist is being called supremely entertaining and the most urgent movie of our time. The AI Doc or How I Became an Apocalyptimist rated PG13 only in theaters March 27.
- [01:01]
Lowe's Announcer
During Lowe's Pro Savings Days, the job works in your favor. Myloes Pro Rewards members buy more and save more materials they rely on every day. Get up to 25% off select molding when you spend $1,000 or more and up to 25% off Pergo Evercraft Laminate Flooring Put Pro Savings Days to work for you. Members get more at Lowe's. Valid through 327. Selection varies by location while supplies last Loyalty program subject to terms and conditions. Visit the Pro Desk or lowe's.com terms for more details. Subject to welcome to the New Books Network.
- [01:34]
Caleb Zakrin
I'm Caleb Zakrin, CEO and publisher of the New Books Network. Today I'm speaking with Cesar Hidalgo, physicist and professor at the Toulouse School of Economics and director of the center for Collective Learning. We're discussing his recent book, the Infinite Alphabet and the Laws of Knowledge. When we look at the products of our modern economy, from novel drugs to towering buildings, we can easily forget the accumulated and diffuse knowledge required to produce them. Bringing together years of research and many illustrative stories, Cesar breaks down how knowledge is initially created, shared, modified, and occasionally lost. For anyone fascinated by innovation, the Infinite Alphabet provides an invaluable framework for thinking through the organizational, scientific, and political hurdles necessary to improve our world. We can understand the sources of knowledge production. We can create better conditions for new knowledge development. Cesar, thanks for joining me today on the New Books Network.
- [02:30]
Cesar Hidalgo
It's a pleasure to be here.
- [02:32]
Caleb Zakrin
This is one of those really fun books to read. I just love a book that is not only interdisciplinary and takes me through all sorts of different subjects and ideas, but also feels useful and valuable in a way. I feel like a reader of this book will. Will walk away from it and feel like they can apply many of the thinking that you do in the book to whatever it is that they are doing in their life, whether it's just in their job or thinking through a bigger topic, bigger issue that they're interested in. So, you know, I really recommend readers go and find the book. It's, it's also, you know, it's. It's. As far as books that are written by academics go, this is a pretty, pretty readable book. So you don't need to be an expert in innovation or economics or physics to be able to understand the ideas that you're putting forward. And I was wondering if you could just start by telling us a little about yourself and your background, because you've had a really interesting career.
- [03:26]
Cesar Hidalgo
Yeah, so my, my background, I'm originally from Chile. I studied an undergrad in physics at Pontificio Universia Cattolica, Chile, between 1998 and 2003, and then I moved to the United States to do a PhD in physics. that time, the hot topic was networks. You know, it was before AI, so it was network science. It was all about the Web. And I did my PhD in physics at the University of Notre Dame with Albert Laszlo Barabashi, which is a physicist who worked on networks. And what was interesting is that during my PhD, Laszlo went to Boston for a sabbatical. And that allowed me to connect with a number of people in Boston at the medical school, people at different parts of Harvard, mit, and so forth. So then I got hooked up into that network. After I graduated for my PhD, I was at the Kennedy School for a couple of years, and then I was a professor at MIT between 2010 and 2019 and recently. But, well, time goes fast. So now, like about six years ago, I moved to France. I now live in Toulouse in the southwest of France, where I'm a professor at the Toulouse School of Economics. And I run a multidisciplinary research center called the center for Collective Learning, which. Which has offices here in Toulouse, but also offices in Hungary at Corvinus University of Budapest.
- [04:46]
Caleb Zakrin
Yeah, the research that you do is really interesting and obviously undergirds a lot of what goes into this book. Could you talk about what your research actually looks like and the people that you work with?
- [04:57]
Cesar Hidalgo
Yeah, so in some way, I'm interested in innovation, I think, because of a couple of reasons. So on the one hand, I had, I think, like a personal story about that I grew up in Chile reading lots of books. And as a child and as a teenager, I always wonder what we lacked in terms of capacities or something that I was missing that implied that people like me were likely not going to be part of those books. So I would read books about great English scientists like Darwin or Newton or Michael Faraday and so forth. And there were no Latin Americans in those stories when I would be reading about these principles, about those ideas. So I was very much interested on the social processes that might lead some places to become more innovative than others. And that's something that I think I always kept in me. But at the same time, through that journey, I think I was able to jump into this field, that very interesting time, because I started working on these topics around 2005, 2006, when I was doing my PhD. And what happened at that moment is that there was a large availability of data that had not been available to previous generations. And what this allowed us to do was to look at systems with a different perspective, a perspective that was much more granular. So if you are a physicist or if you're an economist, you know that one of the ways in which you would do theories is by having variables that aggregate many things. You add apples and oranges, not because you think that apple and oranges are the same, but simply because mathematically it is convenient to treat them as quantities that can be aggregated. But when you have data that is very granular, that has all of these different categories, like data on products, or data on industries, or data on occupations, you can actually think about how to create representations of these systems that honor that granularity and. And that became a field of its own. It's called economic complexity. It's a field that I've been working on for about 20 years. And it's also the one that gives the book, it's titled the Infinite Alphabet, which is this idea that the world is not made of knowledge, as if knowledge was one thing, but knowledge is like this infinite Alphabet, or like a large number of genes on a gene pool that is getting recombined and that gives a lot of dynamics. That also satisfies some principles that we can understand scientifically. But to understand them properly, we need to honor this idea that knowledge is highly fragmented, non fungible, and that makes it hard to diffuse and so forth.
- [07:37]
Caleb Zakrin
In the book, you tell so many stories of how knowledge has developed over time, or how people develop very specialized knowledge. In the introduction, you tell a particular story of an encounter you had at an airport with a Lawyer. And I think this story is so emblematic of the way in which people become experts at certain topics. Can you tell this story and how it kind of represents one of the core ideas of knowledge accumulation that you look at?
- [08:05]
Cesar Hidalgo
So I think that was around 2012, and it was in the middle of the winter. I was in Chicago at the airport, and I was waiting for a flight to Tokyo. We were flying to Tokyo together with many members of the my team faculty to do a big event there. And imagine that this is like 11am on a Tuesday or something like that. I go to the lounge and I'm waiting for my flight, and I see that there's this guy in shorts, like a Hawaiian shirt, having drinks, having fun. So clearly he was not from Chicago, because you're not wearing Hawaiian shirt and shorts at 11am on a Tuesday in the middle of February in Chicago. And we started talking. I don't remember how. And he asked me what I did for a living. I told him. And then when he asked me, when I asked him what he did for a living, he changed the subject. So I was intrigued, you know, why would he change the subject? You know, he said he was a lawyer, but he didn't want to go into it. And then we kept on talking, and he warmed up, and before I left, he says, you know what? I like you. Let me tell you my story. And in the 1980s, Charlie had graduated from law school, and he was practicing law in the state of Florida, and he got fired. So he was living in his apartment. He didn't know what was his life going to be like. And eventually he gets a call from a friend that says, charlie, I cannot show up to court tomorrow. Could you please help me? Could you go to court and extend my case? And in Florida, any lawyer can extend a court case. It doesn't have to be the lawyer that is working that particular case. So Charlie, who is very quick with it, said, okay, 50 bucks. And the word started to, you know, spread that for 50 bucks, Charlie would help you extend your court cases. Also, he started to build a firm that now is called Better Court Charlie. And that people go to not because they're good at extending court cases, but because they are even better than the lawyers that are handling the case, because they know this is specialized process, much better than them. So I use this story to illustrate how specific knowledge can get. Because when you say, well, knowledge about what? In this case, Charlie and his firm have knowledge on how to extend court cases in the state of Florida, which is extremely specific. It's just like a little puzzle piece within a very large puzzle that involves the legal system, but also many other systems as well. And it goes to show that knowledge can be extremely specialized. So we live in a world in which knowledge is highly distributed. And to me, the most beautiful thing about studying the economy is that is the study of how this knowledge is not only generated, but also how it comes together. So that's the idea that gives the book its name, the infinite Alphabet. So Charlie is just one of these little letters of this infinite Alphabet.
- [10:56]
Caleb Zakrin
Yeah. The way that knowledge comes together is really interesting. Of course, if it was obvious, then we would be able to have every invention under the sun, but it's not obvious. So we have to plug away in all sorts of different ways that have different types of people plug away. And sometimes it's the, you know, the desperation that people might be facing like Charlie that leads to these moments of, of, of, of insight where they figure something out that other people might not have have recognized. Economists, you know, for, for a couple hundred years have been trying to understand what the source of the wealth of nations is. You know, there we've, we've gone from thinking that it's how much gold you have to thinking that it's how much, how many goods you to produce. And about 30, 40 years ago, economists started to think a lot about innovation and knowledge as the source of productivity. Could you talk about how economists started to come to this idea?
- [11:54]
Cesar Hidalgo
Yeah. So I think there's two dominant theories, which I would strongly argue are not mutually exclusive, that are now the ones that are most accepted when it comes to understanding the wealth of nations. And this is the idea that the wealth of nation depends on knowledge or human capital, but also that it depends on institutions. And I say that these are not mutually exclusive because they are phenomena that reinforces each other. Now, the way that economists came to think about knowledge as the secret to the wealth of nations comes through the traditional story of economic growth theory, starting with the work of Robert Solow, who develops a model of economic growth that is focused on the contributions of capital and labor to the output of an economy. And when people start doing accounting using that model, they realize that there was output that was not necessarily explained by capital and labor, and that growth was coming maybe from something else, something exogenous. Eventually, this triggers a whole program of research that involves multiple people like Robert Lucas and one of his students like Paul Romer and other people like Philippe, a guy they start thinking about, well, what could that thing be? And one of the key insights Is that, well, whatever that was, has to be something that can be copied without being depleted. Okay? Has to be something that is not like capital in the sense that if I have a hammer and I give you a hammer while you're using it, I cannot use it. Okay? So the capitalist rival, but knowledge is non rival, meaning that if I have an idea and I give you that idea, we now both have the idea. I don't lose the idea because I shared it with you. And rival things cannot grow in per capita terms in the same way that non rival things can. So the idea that knowledge, ideas, information was this non rival input that allowed economic growth. And that's a big contribution by Paul Romer that eventually led to his Nobel prize on, on 2018. So this book follows that tradition, but it follows that tradition from a perspective in which we now look at knowledge not as undifferentiated, aggregatable unit, but one in which it's highly differentiated. And that that differentiation introduces like new puzzles, new puzzles that come from which pieces are complementary because those are going to explain how knowledge is accumulated or in which places it's gonna stick. So that's more or less the intellectual trajectory from the 1950s until this book.
- [14:32]
Caleb Zakrin
In the book you put forward three principles. And these are the principles of time, the principles of space and of value. And all of these consider the different ways that knowledge for time, how to accumulate over time between different groups of people, how one person will learn one thing for another, how in space, how it might go from Silicon Valley, some, you know, ideas that are just being discussed by five or six people in a lab, to then reaching other places around the world, and then also the principle of value as well. Could you just give a quick overview of these principles and how you stumbled upon them?
- [15:12]
Cesar Hidalgo
Yeah. So as I was teaching these, you know, in different colleges and university, I started to, to realize that there was a vast literature that had explored different aspects of knowledge accumulation, knowledge creation that was highly interdisciplinary, but that was also highly quantitative. And that pointed to some very well documented regularities, a literature going back to the 1910s, 1916, more than 100 years ago. So the principle of time is an effort to try to group a lot of ideas that are related to learning curves, which are curves that try to describe how performance changes over time, how performance grows over time, or how costs decrease over time. And this is work that goes back to Leon Thurston, engineer, trained psychologist, that mapped learning curves by looking at how fast people typed in a typing class that he had data from the DAF College of Business in Pittsburgh from 1916. That work, and the work of Theodore Wright, who did very similar work on the manufacturing of planes, helped establish that there was learning in teams or learning among individuals that follow certain mathematical principles. That it was fast at the beginning and then it slowed down. So there was like a law of diminishing returns. And what is beautiful about that work, too, is that even if you look at the curves that thurston drew on 1916 by hand, there's very little scatter between the points. These are not trend lines that are going through a large chart that has a lot of scatter and a lot of variance. But these are tight relationships, the ones that you would expect to encounter in physics or in the hard sciences. But then in the 1960s, there was another principle that was published by Gordon Moore, which showed that the growth of knowledge was exponential, was not something that was bounded. And that opened another puzzle in this literature, which was, well, if individuals and teams learn in a way that has diminishing returns, how can the economy as a whole or an industry as a whole grow in a way that is unbounded or that appears unbounded because it's exponential and these exponentials are sustained for a long time, and that motivates eventually. You know, work on disruptive innovation, which uses multiple learning curves to explain, you know, how they compound into exponentials and so forth. So when I talk about principles, I'm not talking about like clear one line laws that describe everything, but like classes of, you know, statistical regularities that are connected and that we can use to understand these phenomena at different scales. So all of these examples that I told you are about the principle of time. So how knowledge grows over time. But then we can ask similar questions about, well, at what speed knowledge move from one city to its neighbors, or from one industry to other industries that are related and so forth. And there are also speeds and rates that we can measure them as well. And finally, the law of value is about, well, if we're going to put all of these pieces together, how do we know who has the most valuable portfolio of pieces or the most valuable basket of pieces? And we have ways to count that as well. So the book is an effort to try to put these principles in place, not as a way to define knowledge extremely narrowly, but to say, look, we have classes of regularities that we have discovered that are extremely well documented and that can help us explain how knowledge changes over time, how it moves across space and activities, and how bundles of knowledge are valued.
- [18:48]
Caleb Zakrin
I was thinking A lot about it in terms of an idea of you could have two chemists and give them both the same chemicals and if depending on how they add the chemicals together, you can get vastly different results, on the one hand, one, one chemist can develop a life saving drug, on the other hand, so you know, a chemist can develop nothing. So it's interesting to see how you know, this idea, I think is really important that like you can have the same physical goods, you can have the same materials, but the way in which those materials come together, that idea itself is really what can produce the value. And I think that the example that you use at the beginning of the book, looking at these master planned cities and universities like NEOM in Saudi Arabia and these attempts by governments to basically say we're going to concentrate a bunch of capital into developing a space where we can then rival a New York city when it comes to finance, or Silicon Valley when it comes to tech, or Paris when it comes to art. Why do these master planned cities not always work out the way that the planners hope they will?
- [19:55]
Cesar Hidalgo
Yeah, so it comes to these principles and I use those stories to illustrate the fact that on the one hand, governments are behind knowledge as, you know, a goal, but on the other hand, they're doing it in ways that is extremely naive. So if you want to build a rocket and you want to go to the moon, you better figure out chemistry, you better figure out aerodynamics, you better figure out a lot of things because you are going to have to deal with gravity, you are going to have to deal with friction, you're going to have to deal with air resistance and all of that. And when it comes to growing knowledge, you also need to acknowledge that there are certain principles in play that determine how fast knowledge can grow, how fast it transfer from people to people, how fast it can diffuse across activities and so forth. But there are efforts that are relatively recent, like that of Yachai in Ecuador or NEOM in Saudi Arabia, that come with this more fungible idea of the world, that if you have enough resources, you're going to be able to make anything happen. So in a bit of like if you book them, they will come mentality, Yachai was an effort to build a city of knowledge and technological university towards north of Quito that cost the equatorial economy about like $1 billion. That's 1% of their GDP. So it was a huge investment. Neom originally had a budget of about 500 billion. Now I don't know how of that was dispersed or not. No, it is a complicated project, but It's a project that also started with an enormous grand vision. The vision was reduced. The latest that I heard is that now it's being converted into a data center, but a very expensive data center because of all of the investment that went into it in the first place. And this is because these are projects that are very romantic. They are trying to develop knowledge, but they're doing in a way that it's really going against all of the principles. So if you want to develop knowledge, you want to bet on density, you want to bet on the parts of the city that already has the highest concentration of knowledge, because that's the only place that maybe you're going to be able to recombine and generate, you know, new pieces. You want to consider also what are the related activities that you know might be available in your economy. You have to understand that knowledge diffusion, in case that you're trying to attract knowledge that you don't have, is an intergenerational phenomena. So it doesn't happen laterally between peers, but it tends to happen between master and apprentices. And therefore you need to plan for those timescales to absorb knowledge, considering the fact that that's how it works. And unfortunately, a lot of these projects do not consider how it works. So it would be you're trying to go to the moon, but instead of building a rocket knowing chemistry and aerodynamics, you build a sailboat. It's not going to get there because it's not respecting the principles that it should.
- [22:40]
SoFi Announcer
High interest debt can be a real vibe killer. Credit cards, personal loans, and more can make you feel uncomfortable even in the sanctuary of your own home. Well, what if you knew that SOFI could help you leverage your home's equity to feel more at ease? It's called a SOFI Home Equity Loan and it could consolidate your debt at a typically lower interest rate than existing debt with lower monthly payments and all while keeping your existing mortgage rate. View Your rate@sofi.com Pay off debt today Mortgages originated by SoFi Bank NA member FDIC NMLS 696891 Terms and conditions apply
- [23:09]
Botox Announcer
Equal housing lender Chronic Migraine is 15 or more headache days a month, each lasting four hours or more.
- [23:15]
Cesar Hidalgo
Botox Onobotulinum toxin A prevents headaches in adults with chronic migraine before they start.
- [23:20]
Botox Announcer
It's not for those with 14 or
- [23:22]
Cesar Hidalgo
fewer headache days a month.
- [23:23]
Red Bull Announcer
It prevents, on average eight to nine
- [23:25]
SoFi Announcer
headache days a month versus six to seven for placebo.
- [23:28]
Botox Medical Disclaimer
Prescription Botox is injected by your doctor. Effects of Botox may spread hours to weeks after injection causing serious symptoms. Alert your doctor right away as difficulty swallowing, speaking, breathing, eye problems or muscle weakness can be signs of a life threatening condition. Patients with these conditions before injection are at highest risk. Side effects may include allergic reactions, neck and injection site pain, fatigue and headache. Allergic reactions can include rash, welts, asthma symptoms and dizziness. Don't receive Botox if there's a skin infection. Tell your doctor your medical history muscle or nerve conditions including including als, Lou Gehrig's disease, Myasthenia gravis or Lambert Eaton syndrome and medications including botulinum toxins as these may increase the risk of serious side effects.
- [24:04]
Botox Announcer
Why wait? Ask your doctor. Visit botoxchronicmigraine.com or call 1-844botox to learn more.
- [24:11]
White Claw Announcer
This episode is brought to you by White Claw Search Great podcast pick friend. No surprises there. After all, you're all about finding the tastiest flavors out there, just like White Claw Surge. And with big bold flavors to enjoy like blood orange, BlackBerry, cranberry and more. It's time to go all in on taste. Unleash the flavor. Unleash White Cloth Surge. Please drink responsibly. Hard seltzer with flavors 8% alcohol by volume. White cloth seltzer works Chicago, Illinois Right.
- [24:38]
Caleb Zakrin
Yeah, these, these different, you know, thinking about it in terms of the time, you know, how knowledge develops over time, how it diffuses through space, I think is, is really fascinating way to think about it and almost in a way it feels like, you know, different people in a, in the right environment. They're like ad bouncing off one another and you know, generating, generating energy and more potential. When you, when you think about some of the people or the individuals that you, that you profile, you tell some interesting stories about individuals. You know, for example, like you talk about Samuel Slater. Can you talk about him a little bit?
- [25:17]
Cesar Hidalgo
Yeah, so some Slater. It's honestly, he should be way more famous in the US than he is, you know, because he should be like the top guy in the pantheon of entrepreneurs because he's the guy that really started the American Industrial Revolution. So the Industrial revolution started in the UK and it involved not just the manufacturing of textiles, but the manufacturing of the yarn that was needed for those textiles. That was actually really a big binding constraint because people, you know, had looms and they were developing looms, but if you didn't have yarn for those looms, well, those looms were not very useful. And doing cotton yarn was really hard because hand spun cotton was such that if you would pull it too hard, you know, like in a loom, it would fall apart. So hand spun cotton could not be used on a mechanical loom. And there was this race to create, you know, a machine spun cotton that would be strong enough to resist the transition of loom. That race in the 1730s give rise to the first patents. Those do not lead to any successful commercial looms. Then in the 1760s, there's a man by the name of Richard Arkwright that is born north of Manchester and starts developing a system that eventually terminates in a successful cotto spinning operation in the midlands of the uk, in the town of Cromford, where they had water power and together with Jedediah Strat are able to build the first successful cotton spinning operation of the United Kingdom. And that was like a big breakthrough. So when that happens, this starts to spread. We tend to think that nowadays technology moves really fast, but when you study history, you realize that what's happening maybe with cloth today, it happened in some sort of way with other technologies as well. So this starts to spread and they start developing lots of mills around the same area as this knowledge is spreading. And one of those mills was run by Jedediah Strat. And he hires a 14 year old called Samuel Slater that was from the area that by the time that he's 21, had lots of experience working in the loom and had raised to the rank of overseer. And Slater was smart enough to realize that, look, the cat is out of the bag. So this technology is something that is commonplace. Everybody in the UK is going to be able to develop it. I have to go to a place where they do not have it. And he found out that in the US they were looking to attract this technology. Actually there were states that were providing rewards for it, but the UK would punish any attempt to export this technology as an act of treason. So one day he leaves Derby without telling a soul, not even his mom. He goes to London, he boards a ship pretending to be a farmer. About a month later he's in New York and he goes to an attempt to build cotton spinning operation that was happening in Manhattan. He realized quickly that no, these machines are no good. So he ditched the guys after four days and he finds out that there's people in Rhode island that were trying to do this. So he goes to Rhode island and again, imagine this is a 21 year old that had just arrived to the country. He looks at the machines and the people in Rhode Island. Moses Brown tell him, well, if you're able to get these machines Work, you are going to be able to get a fraction of the profits and so forth. They say, no, these machines are no good, no deal. The deal is, I'll build the machines. You have to give me $1 a day to survive. You have to give me a carpenter sworn to secrecy, and a shed where we can do the work. And by October of that year, they had the first cotton spinning operation of the United States. And that is a time. It's close to the time of the revolution. And it's also at a time in which a lot of people were attempting to develop this technology based on hearsay, but none of them had succeeded. So the story of some much later is really important to illustrate that knowledge doesn't travel on books, doesn't travel by hearsay. When it is complex enough, you need to have someone that has experience on it to be able to transmit it. And otherwise it's not going to take root. And once it took root, the same thing that Samoslady had observed in the midlands of the uk, it started happening around Pawtucket and around the rivers of Rhode Island. A lot of mills started to sprung up. Eventually he retired because he knew that this was going to become tough competition. But he had made it, and he made the northeast of the United States and an industrial hub.
- [30:02]
Caleb Zakrin
Right. It's interesting, you talk about the difference between knowledge of facts and knowledge of processes. How do you put this emphasis on processes and on just really ideas and action? So putting different facts together and different assemblages then leads to the outcomes. We can know all the facts that there is, but it doesn't necessarily mean that we can actually create words. Like, I think the infinite Alphabet idea or the kind of the analogy is like, we could know all the letters, even if we know all the letters, even if they're infinite, doesn't mean that we have sentences. We're not creating paragraphs, we're not creating novels. We have to actually know how to put them together.
- [30:43]
Cesar Hidalgo
Exactly. So one distinction that I introduced relatively early on in the book is the distinction between factual, conceptual and procedural knowledge. And one way to understand that distinction is by using the detective story as an analogy. So when you look at a detective story, usually you have a very straightforward plot. At the beginning, there's a body and the detectives come into the scene and they say, oh look, there's a bullet hole on the wall. Or there was a phone call that was placed at 2am last night and what they're collecting there is factual knowledge. The bullet hole doesn't tell them who committed the crime or why the phone call. But they're facts. And usually the hero of the show is this genius that is able to transform all of those facts into what would be called conceptual knowledge, like some sort of theory or story that puts them all together and they don't get it right the first time. Sometimes they accuse the wrong person. It's kind of like a tough process. So they need to prove that that story is the right story. And for that they use procedural knowledge. So let's say they send some DNA sample to the DNA lab and that's a procedure that allows them to verify whether the DNA match that of the suspect and so forth. And those are three different types of knowledge. And we tend to use the word knowledge for all of them. But they satisfy very different diffusion dynamics. Like factual knowledge is very easy to diffuse. It's very easy to teach, you know, people in the world, you know, what's the capital of the United States or the capital of France, those facts, you know, do not have an issue. Diffusing procedural knowledge is much harder to diffuse. Developing, you know, let's say a nuclear power plant, which is a tough process, you know, is something that would not happen through hearsay or just by the diffusion of the idea, would require, you know, teams with experience being able to be redeployed in different locations and teaching, you know, people through that hands on interaction. So if you don't differentiate between these different types of knowledge, you might get confused. You might think that knowledge can diffuse easily because some forms of knowledge can, like factual knowledge, when there are other forms that are extremely hard to accumulate or to diffuse. Like these more complex procedural forms of knowledge.
- [33:04]
Caleb Zakrin
Yeah, talking specifically about, you know, the type of knowledge that is produced at universities, produced in the ivory towers, you know, everyone knows that, you know, academics are supposed to specialize really, no matter what their discipline is. If you're in economics, you're probably spending 90% of your time talking to economists and even that in your narrow subfield of economics, if you're a physicist, you're talking to other physicists, you're biologist, you're talking to other biologists. Yet you've had this interesting career where you've worked with people in all sorts of different disciplines. Can you talk about what that experience is like going through these different disciplines and sort of seeing how that impacts the way that you think about ideas and just the challenges faced in terms of connecting good ideas in one discipline and bringing it to other disciplines, what that challenge looks like?
- [33:53]
Cesar Hidalgo
Yeah, so I, you know, I Think I decided to become an academic because I love creativity. So I was attracted to the creative side of academia, which is not the most common side of academia. I think there's a lot of academia that sometimes is about, you know, specializing, as you say, in something, you know, very precise, and making sure that you do the best version of a procedure for a particular, you know, process or a particular field. But I love that creativity. So I've been at a school of architecture. I'm not at a school of economics, I've been at a school of government. I've been at the department of physics. And it's interesting because in all of those places, people do amazing work and they do great work. But also all of those places have strong differences in things that are quite human, but at the same time underlie everything that gets done. Some sort of aesthetics, as we might want to call it, what is considered a valid question or an interesting project or what is the right way to communicate or to present an idea. And people that have not been across many disciplines tend to think that they're right ways of doing things. And in reality, there are many right ways of doing things. And when you are in different disciplines, you realize that there are differences that are useful for a reason. So it is hard to communicate ideas across disciplines because you need to translate them not only in terms of communicating the concepts, but changing the format and adapting the forms to some sort of culture or dance that is a specific to a certain field. Some fields like to go directly to the results. Other fields, they expect half an hour of introductions and caveats. Some fields want things that are tangible and they don't care about ideas like what were you able to build or do. And in all of those cases, they might have issues valuing work that is not done according to that canon. So I think that translation of forms is one of the ones that is the most challenging. And for that is actually very useful to have insider friends in each one of the disciplines that can shepherd you or be your Sherpa in that process to help bring those ideas around. At the same time, I think in all fields, there's people that are more open or less open to ideas. So you need to find who are the people that are more receptive. The diffusion of ideas is difficult, and you don't want to waste all of your time and energy on people that might never accept your ideas or might never be interested in them. You want to team up with those that can. That brings us to the concept of absorbing capacity, which is an important concept in the diffusion of knowledge. But you need to find the ones that are interested, but also capable of taking a hold of the idea and then continuing to develop and in the context of that field.
- [36:47]
Caleb Zakrin
Right, yeah. One of the puzzles that you look at in the book is something that has just transfixed me for years now, ever since I first really started to learn about it, which was the mechanics of the European recovery after World War II. You look at how Europe after it had been absolutely decimated in the wake of the war, how it developed through these institutions like the imf. And this is a sort of a story tell. You look at it, you look at how it worked, how it didn't work, what some of the knowledge and lessons were. But I think that this is a really important story and just understanding what leads to economic development. So can you tell this story of the post war European recovery and some of the lessons that we have learned from it?
- [37:31]
Cesar Hidalgo
Yeah. So at the end of the Second World War, there was an effort to redevelop Europe. That was a primary importance because the development of Europe was not a charitable thing to do. It was politically important because the European recovery was needed to bring stability to the region. And also this in the context of the beginning of the Cold War, where they're competing world models about how nations should organize themselves. And the United States played a very important role in European reconstruction, creating a number of institutions that lent money to European countries like the Netherlands, France and so forth to support the reconstruction and development. And the thing is, that process was extremely successful. It was so successful that then people said, well, if we can rebuild Europe with loans, maybe if we lend money to Africa, to Latin America, or to parts of Asia that are underdeveloped, they're going to develop as well, and we're going to be able to do something that is good for the world and even make a profit doing it. So I'm kind of doing a bit of a caricature here, but I want to kind of show a little bit where that success left the mood of the people that were doing this type of effort. And then these international development institutions started lending money to developing countries and they did not get the same results. Of course, Europe was extremely rich in knowledge. So I have stories in the book, for instance, of how the Piaggios and coloradino lascanio developed the Vespa from the ashes of the aircraft industry in Italy. Now, if you go to another country, yes, they might not have the factory the same like in Italy, because in the Delhi was bombed in another country they didn't have it. But in the case of Italy, they still had the knowledge. So they were able to rebuild because it was very rich in knowledge. So that money was coming in to a place that was very fertile and that was able to rebuild itself because of the knowledge that was available in the population. So then that led to kind of like a whole crisis within international development community, which is, well, maybe money is not enough, so there must be something else going on. So, okay, it must be institutions. It must be reforms. And they started to ask in the late 80s and early 90s for these economies to reform as a condition to accept the loans. But that program has not been as successful as well. So there are many countries that have been star reformers, but have not been star performers, because a lot of these institutions can be adopted in a very performative manner. So you change how everything is supposed to work. But in reality, formal institutions, in my opinion, are rather weak compared to culture, which is what underlies the way that society operates. So we kind of went full circle from thinking that development was easy because in the aftermath of the Second World War, Europe was able to recover very quickly, had extremely fast growth rate, and this growth rate was in part financed by loans to understanding that, well, finance was not enough and institutions maybe were not enough. And I use that to set up examples of development that have happened in context that they did not have neither the institutions nor the finance. These are stories like the one of Chen Chongqiang in Zhongwanzhong in China.
- [41:08]
Caleb Zakrin
Yeah. Could you talk about that example of China? Yeah.
- [41:11]
Cesar Hidalgo
So in the 1970s, China was very poor for global standards in terms of GDP per capita, was one of the poorest countries in the world. But, you know, in terms of knowledge, they were not doing that bad. You know, an example of that is that there was a Chinese physicist by the name of Chen Chun Xiang who had studied, you know, in the Soviet Union and had built the first tokamak reactor, you know, in China, in Beijing. A tokamak reactor is a type of nuclear fusion reactor that is used in experimental settings. So that's not an easy machine to build. You know, that's a hard machine, you know, to build. You need a lot of knowledge to be able to build one of those. You know, the guy that developed it in the Soviet Union, Sakharov, was a Nobel Prize winner. And Zheng Chengquian, because of his accomplishment developing this fusion reactor, was invited to the United States in a team of four people. They went to Princeton, they went to Boston. I think they also went to Stanford. And they wanted to see how Americas were building, you know, fusion reactors. And originally they thought that this was a technical visit. But what happened is that when Chen Chun Xian went to the United States and started to realize how Americans were building the reactors, he imagined that the US Being so rich, had, like, these big giant factories with lots of workers doing the parts that were needed for this experimental plasma fusion reactors. And what he realized is that these were all the small startup companies. A professor and six students, 12 students, very small operations that were building this specialized equipment. So when he went back to China, he went back not with knowledge of a technique, but of a social technology, which is like, no, what we need to do here to develop is to have professor entrepreneurs. Would it allow the people like me and others that are here in these neighborhoods of Beijing, close to Tsinghua, Peking University, Chinese Academy of Science and so forth, develop our ventures outside the university? He eventually gets kind of like a small permit to do activities on the weekend out of a warehouse and everything. But the system starts closing in on him, and he becomes ostracized. And he also becomes a center of attention because he had been going around the area telling everybody about professor entrepreneurs. He was the first one that is allowed to kind of have one of those operations. But then he's getting hit with audit after audit from institutions that were not open to this idea, because they say, well, you're using those pliers. Those pliers were paid by people's money, not your capitalist dreams of having your own enterprise and so forth. And so everybody was looking at him, and they were not gonna attempt doing a venture if he was going down, okay? And he's basically, you know, on the ropes, you know, by the end of, I think, 1982 or 1983 in the book, I have the right dates. And he gets a lucky break because one of the persons that had been championing him is married to someone that would write a book bulletin that was read by the hundred top officials from the politburo. And together they come up with a story that talks about this successful experiment in innovation and entrepreneurship happening in Chongwangzhong in Beijing. And that makes it to the 100 top members of the Politics Bureau. This is after Deng Xiaoping had entered China, had started those reforms starting in 1978. So they see this as one of the examples that they wanted to push and develop. And basically, they politically protect him. They say, okay, Chen Xujiang is safe. Don't mess with him. Don't push him any longer. And when that happens, there is an explosion of entrepreneurship that starts appearing in Chongwangzhong because people that were working in computers and were like Lenovo and other companies come out from that era, from that place. And one of the things that is important about the story is that yes, there is a role that is played by institutions there. Of course there was Deng Xiaoping's group that was already participating of the highest feat of the party as well. But the ones that were demanding that change in institutions were not guys that were selling oranges at the traffic light. There were guys that had built plasma fusion reactors and they were advocating for professional entrepreneurship. So to have the push of the institutions that you would need for growth and development, you need those highly accomplished knowledge workers to be the ones that are making that push, because they are the ones that know where the shoe is tight and where it needs to loosen up. So it's an interesting story because it's not institutions first, it's not capital first. It is kind of like pure hardcore entrepreneurship in an adversarial environment. And I love that story. There's a few others, but I think it's one of the best stories in the book.
- [46:29]
Red Bull Announcer
It's crunch time at work and you need to bring wings to your workday. Visit redbull.com gettingitdone and answer a couple questions about your work style to get a Spotify customized playlist tuned to your productivity. Plus, score a can of Red Bull on us while you go from to do to done. And remember, Red Bull gives you wings. Supplies are limited. Terms apply. Visit the website for more information.
- [46:55]
Botox Announcer
This episode is brought to you by Indeed. Stop waiting around for the perfect candidate. Instead, use Indeed Sponsored Jobs to find the right people with the right skills fast. It's a simple way to make sure your listing is the first candidate. C According to Indeed data, Sponsored Jobs have four times more applicants than non sponsored jobs. So go build your dream team today with Indeed. Get a $75 sponsored job credit@ Indeed.com podcast. Terms and conditions apply. Starting a business can seem like a daunting task unless you have a partner like Shopify. They have the tools you need to start and grow your business. From designing a website to marketing to selling and beyond, Shopify can help with everything you need. There's a reason millions of companies like Mattel, Heinz and Allbirds continue to trust and use them. With Shopify on your side, turn your big business idea into Sign up for your $1 per month trial@shopify.com specialoffer I
- [47:52]
Caleb Zakrin
think it's interesting when thinking about the, you know, the policy considerations, you know, you give these examples of, of these state led initiatives to try and produce these innovative universities or innovative cities and how sometimes it doesn't work when it's, you know, exceptionally top down. But then of course there's this issue. It's like, okay, if we know that on some level innovation is being driven by these kind of random interactions between smart individuals who have some, you know, novel insight, it doesn't necessarily seem like the solution is then, oh well, we should just have the government identify these smart individuals and give them money. So is there any actual policy advice that you could give to Saudi Arabia or these other countries that are trying to match Silicon Valley or match New York City or match Paris?
- [48:46]
Cesar Hidalgo
So there is actually, and I have some of that in the book, I have an article coming out in a newspaper in Italy also using some of the stories in the book about that. And I think there's a few things. Governments are going to want to intervene. So the question is how to make sure that they intervene in the best possible way. That desire is going to be there. And the key thing that we need to remember is that there are dynamics of capitalization that are different than the dynamics of redistribution. For example, here in Europe, where I live, the idea of redistribution is extremely important. The pension system here in France is not a system of capitalization, it's a system of redistribution. Some people pay for other people to get it, but it's not that money is getting invested in some account and it's accruing over time and so forth. And knowledge is a form of capital that accrues and accumulates according to a capitalization dynamics. So if you're in Ecuador and you say, I have a billion dollars and I want to develop a city of knowledge, and what you're going to do is you're going to start building buildings in the middle of nowhere that have no resale value. You're going to run out of those billion dollars very quickly and you're just going to have a bunch of concrete and rebar that is getting weathered and is not doing very well. So what you want to do instead is grab that billion dollar, put them in an endowment and use the payout of that endowment to start financing chairs that would be not for five or ten years, but forever. So let's say you have a billion dollars, you put it at 4%, that's 40 million a year forever. And then with that 40 million you say, okay, we're going to open 40 excellence chairs in which we're going to attract scholars to Ecuador and they're going to have a $1 million a year research budget, let's say for 20 years. Okay? So they can come here and if they need to rent space, Quito has a lot of nice buildings. Rent space there, or there might be universities that are interested in hosting some of these, you know, chairs. If you need to hire an admin, hire an admin. If you need to buy a computer, you want to hire postdocs, put another link in hire postdocs, because you're going to be much better at attracting them than we are. And then you are investing the money in people that would be highly vetted. This is kind of like going to. When you're trying to get players for like a big team, you're kind of like going after the big players and you empower them to develop those capacities in your country. Now, the nice thing about that plan is that if after 20 years you want to cancel it, you still have the billion dollars. It's not a bunch of buildings that are being destroyed by the weather. So you have dynamics of capitalization. And in China, they did something similar to that. They created these guiding funds. It's a very interesting story. It's a fund in which the government puts a fraction of the money and then the privates complete the fund. But the privates have the option to buy the government shares at a capped price if the fund succeeds. So basically what they do is they do a fund that give privates an even better asymmetric upside. By doing that, they can nudge investment into certain sectors without being, you know, so authoritarian about it.
- [52:08]
Caleb Zakrin
Yeah, that's, I think that, that, that's a really interesting idea. And it's especially, you know, interesting, I think, putting, you know, investing in buildings versus investing in people. There's obviously so much discussion always about infrastructure and how obviously some places have different infrastructural issues. And, you know, sometimes building a bridge in a place like, really is like the key to, to economic development. But I think for the type of, you know, long, long term, you know, almost moonshot innovation projects that like, really move the dial, like investing in these sorts of people is. Is. Makes the most sense. Especially, you know, just bringing someone that, that has some knowledge to a place, the students that they will interact with, you never know how it will yield in 20 years. And that's part of, part of what's interesting about it is it's very unpredictable. So I'm wondering if you could just talk a little bit about, like, you know, the, you know, how this, how, how this can be modeled in a way, because in a way, it seems like it's almost impossible to predict how the investment pays off to a certain extent. You kind of just have to have faith that, okay, like, if we, if we invest in enough individuals over a long enough period of time, eventually it will yield. But, you know, isn't there some concern that maybe it won't lead to anything? At least if you invest in these buildings, you know, you might, you might have a place that people can move into in 20 years.
- [53:30]
Cesar Hidalgo
So, well, to the buildings, it depends on, you know, where they're located, of course, because if they located in a very remote place that there's nothing else. For example, in Yachai, even to this day, they bring water on cistern trucks. So there's no really water system. So not even, you know, as real estate, they work. But also to the buildings. One of the things about Silicon Valley history is that, or the history of at least the tech sector in the US Is that all of the big companies started in a garage or a strip mall or very modest buildings. Like Shockley Semiconductor also is kind of like some dinghy lab in terms of the infrastructure. So it's funny that when countries try to imitate Silicon Valley, they try to imitate kind of like the late stage of it with nice open sparks, like the Apple campus, whatever. No, like, you didn't need that. It comes, in fact, because of that frugality in which people are doing things in the weekend in the garage. So that's one of the things that I would say about that and in particular the buildings, because I think it's so obvious after the fact. Everybody knows that Silicon Valley is full of famous garages, but still the attempts that are put out there tend to be. They don't want to cut ribbon in front of a garage with a genius. They want to cut ribbon in front of a beautiful building that might not have the people instead. Now, the other question that you had was about predictability. And at the, let's say, individual or instance unit might be very hard to do. It might be very hard to predict. Well, if I invest in this person, will this person be the one that succeeds or this city? But at the statistical level, at the more aggregate level, we have principles that are actually quite robust, like the principle of relatedness. So if you have a data set on hundreds of cities or hundreds of countries and you look at all of the activities that they're engaged in, you can do models that are relatively simple and that are very good at predicting the probability that an activity would grow or would decline in that location. And this is because knowledge flows tend to occur also between activities. So the places that have clusters that reinforce each other tend to have, let's say, kind of like a positive momentum. And people that are isolates or firms that are isolates within their ecosystems then tend to suffer a lot of the cost of not having those other spillovers. And you can characterize that very easily using recommender systems similar to the ones that we use to predict which movie a person is going to like or watch, but apply to economic data. And this is a big area now in economic geography for the last 15, 20 years, because it's easy to do and it's so robust that it has moved from a variable of interest to a control variable, because now it's something that you have to include as you explore other ideas.
- [56:36]
Caleb Zakrin
I almost hesitate to ask this question because I don't really like asking people to make predictions, But I've seen so much discussion around how AI is just going to make these sort of knowledge workers almost irrelevant. You know, I've already seen layoffs in certain things, or at least, you know, increased efficiencies, where software engineers, you know, can execute a project in a day that would have taken them a month. You know, I still believe, or maybe it's a hope on some level that human creativity, you know, will stand in some shape or form at the forefront, even augmented, even if augmented by these AI systems. But how do you think about artificial intelligence as impacting some of the ideas that we might have about how knowledge diffuses and grows?
- [57:27]
Cesar Hidalgo
So AI is very interesting because I've looked at the impact of many technologies in the diffusion of knowledge or ideas. But so far, all of the technologies that we had are communication technologies. Communication technologies, not embodied knowledge in the way that AI does. So a book, it's a great way to communicate ideas, but you're going to have a conversation with a book.
- [57:53]
Caleb Zakrin
Book.
- [57:53]
Cesar Hidalgo
So AI is the first technology, I think, in human history that has that embodied capacity that is similar to that of humans, that you can have a conversation when you have a command line, AI, like Claude, it even feels like you are talking to a colleague and so forth. So what I think that does is that it is a technology that therefore is very complementary with people that have the right skills to be able to, you know, make the best out of it. You know, because like all technologies, you know, a brush doesn't make you Michelangelo, and a guitar doesn't make you Jimi Hendrix. It's about, you know, how well you can use the brush, how well you can use, you know, the guitar, and how well can you use the AI? So I think people that are smart, have lots of ideas, are entrepreneurial and so forth, are getting supercharged, you know, by AI and people whose job prospect was like, I might become a guy that cleans data, but someone has to review my work, you know, to make sure that I didn't make mistakes, are in a very difficult and different position. So that's what I think is happening right now, that there's some particular individuals or sectors of the economy where those individuals concentrate that are going to boom and there's people that are going to struggle because their job definitely is something that might be easier to ask to an AI than to send them a request on Slack, you know, and that's kind of like, I think the trade off that a lot of people are doing. Should I ask an employee or should I ask, you know, an AI when I have this idea or when I need this logo designed, or, you know, when I want to develop this snippet of code or all of that stuff like that. And that trade off is something that is depending also on who you have on the other side, you know, to ask to, you know, like, are they like really smart so they want to give me something better than AI, or is this someone that often makes mistakes and therefore it's going to just be like a tax on the production process. So that said, I do think that people have a drive, that it's very human, it's very internal, and we all want to be productive and we all want to find our place in the world. So even though finding a place in the world can be hard for many people in the world of AI, they're not going to stop trying. And I think part of the solution is going to come from, sure, the creativity of the entrepreneurs, but part of the solution is also going to come because people are hopefully not going to give up and are going to keep on trying and they're going to find ways of becoming useful towards others as we transition into this more creative economy, which is something that we say that we always want, but it's ruthless. They're going to find ways of helping out in a team, maybe doing more social activities in which they're connecting with others or organizing events or doing things that where human, have more capacity and that might help the creatives that are getting supercharged in that process. So I do see kind of like society organizing into kind of like this sort of different way in which you're going to have teams organized around a few creatives. The creatives are supercharged by the AI and are doing 157 different projects. And then there's other people that support and help. And a lot of that comes from their own initiative. And I think there's room for emotions there. We want to find room for other people and we want to help them out, and we want everybody to be able to have a life. And as a scholar and as an entrepreneur, I use that consideration a lot. And I can be tougher with the people that are really smart because I know that they're gonna pull through. And for the ones that sometimes struggle, I'm happy to give them a pass and make it easier for them or try to figure out ways to include them, even if it's for a period of time, so that they can continue to be part of society, they can continue to be connected.
- [61:50]
Caleb Zakrin
Yeah, I think that's actually a lot of how I imagine organizations changing that. There is a lot more work that's going to be done by one or two individuals that essentially, rather than having a team of 20 people helping them, they're using AI bots to assist them. It doesn't mean that those people are necessarily going to go away. Obviously, some people are. Are going to be, unfortunately, in those contexts, made redundant, and they'll have to be a, you know, some issue that the. That will. Will have to be dealt with in the future. But, yeah, I certainly think that there will be a. So more of a social component for a lot of people for their jobs in the future where, you know, they do other things, talking with the person, just almost like a Socratic dialogue, just to get them thinking, asking questions in the same way that they might be engaging with the chatbot. So, you know, I certainly hope that, you know, as the work world changes, as we have more knowledge and we use these tools that, that augment us, that we. That we find a way to include as many people as possible, you know, so that they feel like they are contributing, but also so that they are contributing in the best way possible.
- [62:53]
Cesar Hidalgo
So. So let me make a point about that, which I think it's. It's simple, but it's profound, which is. So I have a relatively large team and I work with people, and I'm working a lot with AI right now, too. And there's something that AI cannot give me, which is meaning. Okay. And what I mean is not meaning in the context of interpreting a sentence. It's Meaning on the value of my work. So, for instance, one of the. You probably communicated with Veronika to coordinate this meeting. No, Veronica, she works at the center for Collective Learning. And I feel like we're partners in crime, in anything, because we're like, okay, we have to edit the website, we have to organize this event, we have to do this, we have to do that. And to me, it's not just about doing those things. And if I were to do it with an AI, it wouldn't have that meaning, because the meaning, I think, comes from the fact that we're accomplishing things together. And there's a feeling associated with that. And that I think is important. So it makes those soft skills, but that. That emotional connection to other people at work very powerful. Because if I were doing all of these things just alone with AI, I would stop doing it. I would lose my motivation because they would be meaningless. So that meaning component is the secret.
- [64:05]
Caleb Zakrin
Yeah, absolutely. And I feel like that is what provides people with the. Like you said, it provides people with the motivation to keep going. And it's really part of the excitement of it, and I think the excitement of the stories that you relate in the book, and there's. There's dozens more that we haven't had the chance to talk about. But part of the excitement of these stories is the contingency, the randomness, the essentially like the pinball nature of people bouncing off one another, sharing ideas, having random experiences that then they are able to utilize years down the road without even recognizing it. So, you know, it's really exciting in a way. Like, I love the, you know. You know, in our world today where there's, you know, we don't know if, you know, if there's a 25% chance that AI will lead to some, you know, large catastrophe there. There, you know, it's fun to think about, like, the. The excitement of knowledge and innovation and the. The real, you know, incredible things that we've been able to develop in the past few years through randomness over long periods of time. Like, you know, even if you just look at like, the development of like, GLP1s, like Ozempic, it took decades for those drugs to be developed through all sorts of different research that nobody knew that, you know, studying types of venom that would lead to the. The discovery of these drugs. So it, you know, it's. When you. When you dig into these stories of innovation, they really are just absolutely amazing.
- [65:26]
Cesar Hidalgo
Yeah, the same with, like, COVID vaccine. You know, it was. There was a great book called one shot to save the world. And it's, it's a nice, excellently written book, like, you know, like one of these professional journalists that really knows how to write well. And it takes the story back like 40 years and how everything was being developed slowly and with a lot of friction and resistance. So it's also like a story of entrepreneurship against all odds, because this was not built with some sort of intention that was going to be useful at the end of 2020. It was people kind of pursuing curiosity driven ideas and ideas that at some time were kind of like a little bit radical. This idea of injecting RNA was a stupid idea because when you inject rna, everybody would think, no, no, your immune system is going to make sure that that shit doesn't survive. It's too dangerous. And they were able to eventually figure out how to do it. So they were really pushing against the grain. So you have examples like that. And I think in the social aspects you have that as well. As an entrepreneur, I, I learned that usually someone that says no today might be the one that you're doing a project three or four years down the line. So always keep your doors open because things change more than you want to believe. And the paths are always circuitous, they're never straight.
- [66:56]
Caleb Zakrin
Yeah. And your book does such a great job of laying that out and I really do recommend anyone who's interested in, you know, how innovation occurs, how knowledge develops. We'll find, you know, a lot of entertainment in this book and, you know, the stories will definitely stick with them. So. You know, Cesares, thank you so much for being guest on the New Books Network. It was really wonderful to get the chance to speak with you about your book. I really enjoyed our conversation.
- [67:21]
Cesar Hidalgo
Yeah, thank you, Caleb. I also enjoy the conversation very much and I hope the, the listeners enjoy it as well.