MM: So I read this book called Red Notice by Bill Browder — it’s his story of investing in Russia and taking on the oligarchs of Russia, and it’s this non-fiction thriller. It turns out his father, Felix Browder, was the chair of the math department here for a while, so I was fascinated by the connection. So I’m curious to hear about your interaction with him.

CK: I was very fortunate to meet Felix Browder, so maybe I’ll say a few words as to the circumstances of getting to know him. I was very young, 19 years old. I had left Argentina at the time of the political upheaval there, where the university had ceased to function. Some of my teachers suggested that I come to the United States, and they wrote to Alberto Calderón, who was at that time a professor at MIT and a close friend of Felix Browder.

And Calderón then communicated with Browder about me coming, and I didn’t have a degree. I never got an undergrad degree. And Browder was very kind and agreed to meet me. This was September 1973. So I went to his office, and he said, well, let’s see what you know and what you don’t know, so he gave me an impromptu exam. And he asked me lots of things; I knew some, but I mostly didn’t know them. And since I had no degree, he said the only thing we can do is have you be a student at large for one year, and then we’ll see what happens.

But he spoke with people at the admissions office, and they said that since I had no degree, I had to also take some courses that were not math. So I took the freshman sequence in humanities and the freshman sequence in social sciences and I took three math classes at the same time, and I had to work very hard.

At the end of the year, things went well, so I went for the summer to Argentina, and I received a letter from the department saying that I was admitted to graduate school as a graduate student, and they got a fellowship for me. And this was all done by Felix Browder.

And through the years, I had interactions with him. After my post-doc at Princeton, I went as a tenure-track faculty to the University of Minnesota. And I was there as an assistant professor. And after a year, I was promoted to associate professor and then to professor. And then around ‘84, Browder approached me to see if I would be interested in Chicago. I said yes, I would be interested. Eventually, the department made me an offer. I accepted. In the fall of ‘85, I came to Chicago.

At that point, Felix had resigned as chair of the department and moved to Rutgers. And after that, I saw him a few times, once at Rutgers, when there was a conference in his honor, and I was very happy to see him.

But when I was at Chicago as a student, I was close to Bob Fefferman, who was a junior faculty and I was a graduate student, and we were working in very close fields. And he was very close to Felix and his family, so I got to know both Browder boys. I got to know Bill and his older brother, who’s now an astronomer in Hawaii.

MM: You said you came to the US when you were 19. Were you always interested in math? Can you reflect on your interest at a young age?

CK: Yes. So I first became really interested in math when I was 12. This was my first year of high school. You know, the educational system is different in Argentina, there’s no middle school. You go from elementary school to high school.

In my first math class in high school, I had an excellent teacher. He had a Ph.D. in math, he was from Chile, and the class consisted of Euclidean geometry and he taught us to prove things. So the class was about proofs, facts about triangles. And then I realized that my mind worked the same way as mathematical proofs. So from that point on, I got very interested.

But when I finished high school, my family and my math teachers all told me, you shouldn’t get into math because you will starve. The jobs in math were very ill-paid in Argentina. It was very difficult to have a career at that point in math in Argentina. So I started studying engineering at the University of Buenos Aires. But at the same time, I also studied math. And after the first semester, I was completely disgusted with engineering because it wasn’t rigorous. So I stopped engineering after my first semester; the second semester, I just continued in math; and then I had the third semester. And then after that, I came to Chicago.

MM: I want to hear about your experience at Chicago. You took classes with Alberto Calderón and Antoni Zygmund. Can you reflect on your experience with that? And more broadly, it is known as the Chicago School of Analysis. For someone who is not familiar, what was that?

CK: When I first met Zygmund, he was 73 years old — almost my age now! And in my first year, I took a measure and integration course from him. He wrote — at that point it wasn’t even a book — it was lecture notes that eventually became a book, and I enjoyed it very much. And he was very kind to me.

And when Calderón came back to Chicago the following year from MIT, I took a class from him on some recent work of his in harmonic analysis. And then I became interested, so I started going to what was then called the Zygmund Seminar. It was once a week at 3:45, which is the time that we’re keeping to this day. There were two seminars: one was expository and the other was research. And of course, at the beginning, I didn’t understand anything. But slowly I began to understand.

Let me say a few things about the Calderón–Zygmund School. So Zygmund was one of the premier analysts in the first half of the 20th century. He worked mostly on trigonometric series, Fourier series, and real analysis, but only in one variable, so his aim was to try to find the theory in higher dimensions.

In the late 1940s, he went on a visit to Argentina. What happened is after the war, the US State Department wanted to promote scientific development in the underdeveloped world. They sent Zygmund to Argentina, where he met Calderón. He was his teaching assistant in a class he taught. And Zygmund was of course extremely impressed with Calderón, so he arranged for him to come here to do his dissertation.

Calderón was an engineer before this. He was an amateur mathematician because his father was dead set against it. But he came to Chicago and after 2 years, he finished his PhD, which consisted of 3 new research articles that opened the way to analysis in higher dimensions. That’s how the Calderón–Zygmund collaboration developed. They wrote many papers together and opened up a whole new school of mathematics. It’s been influential for many years.

MM: Can you reflect on the Honors Analysis course that UChicago Math has become famous for?

CK: Yeah, that is the creation of Paul Sally, who was one of the young faculty members when he first came to Chicago in the mid-70s. Eventually, towards the end of my studies, he became the chair of the department. And he was somebody larger than life, he was a real character; the students loved him and feared him.

And he developed this class, which is called Honors Analysis, which was to attract the top undergraduates and teach them really high-level math and very advanced things. And, in fact, my next-to-last year as a graduate student, I was the teaching assistant for that class, which I enjoyed very much. Jerry Bona was the teacher, he was a young faculty member. And I remember one time when I got stuck on homework problems that we had assigned, I had to ask for his help and he was extremely amused about it.

MM: Can you reflect a bit on what does mathematical research involve? You have made so many tremendous contributions, oftentimes in collaboration. What is the collaborative process like? Do you remember any of the moments where you had an epiphany, and what does that moment look like?

CK: So after my post-doc at Princeton, there I had my first really serious collaboration with David Jerison, who is still my collaborator now. We just published a paper together, and he’s exactly my age. And I enjoyed that very much. I was an instructor, he was a graduate student, because he had taken 2 years off to go to Paris to learn math there. Anyway, so we worked very hard together, and we got some success.

But when I went to Minnesota, I collaborated with, and was sort of mentored by, Gene Fabes, who was a former student of Zygmund’s at Chicago. And he was a sweet person. And in his work, he always worked with others. He was a very sociable person, and he enjoyed the process of discussing with somebody else. And I learned this from him and I’ve done it ever since.

When you’re in math as a researcher, you have to go really deep into the subject and spend many hours thinking and working. But if you’re doing it with somebody else, then you have a social outlet for your work, and that is a very nice situation. And the other thing is that in conversation with somebody else, you sometimes generate ideas that you didn’t know you had, and they come out. And you don’t know how they came out, but they come out. And that’s part of the pleasure of the collaboration.

I have had moments of inspiration, yes, and it comes as a flash. It’s not a conscious thing. I’m wondering about something, and then suddenly I don’t know from where some idea comes. When I was younger, it used to happen during the night, or sometimes first thing in the morning in the shower. Now I’m too tired, and so it comes later on.

I remember one of my collaborators and co-authors was in Spain, and we were working with a friend, Gustavo Ponce — this collaboration started in 1987 — and we had been discussing with Gustavo, and Gustavo had to go back home. And Luis and I started discussing, and then suddenly, I don’t know how or why, I had this vision of how to do it. And then I could see the whole problem, and it was really extremely satisfying. One moment you’re stuck, and then the next minute I saw the path.

MM: You mentioned these social interactions and collaborations. You were president of the International Math Union and vice president of the AMS before that. Could you explain what your role was? And you were chair of the Fields Medal Committee, so what was your role there?

CK: The role of vice president of the American Math Society is basically you attend meetings of the Council of the American Math Society, and you give your opinion on the matters that are discussed.

Being president of the International Math Union is a job of tremendous responsibility. It’s supposed to steer the development of math interaction all over the world in both research and education. And, of course the decisions get voted on, but you are the generator of the initial proposals.

So, during my period as president of the IMU, there were two very cataclysmic events. The first one was COVID. The IMU is built to generate the interaction of mathematicians from different countries. COVID was the anti-IMU. On the other hand, we were very lucky that Zoom was developed, and there was a possibility for online interaction. So that saved the day. It meant that we could do many, not all, but many of the activities that we had planned.

But when finally COVID more or less was resolved, we had the centenary of the IMU. So there was a celebration in France at Strasbourg, which was the place where the IMU had first been founded, and we had a meeting to celebrate this. People came from various countries, and the meeting was finally held in 2021.

It should have been held in 2020, but we had to postpone it due to COVID. And people were so happy that we were finally able to meet together and discuss, make math presentations and talks. We had the idea of having 15-minute talks on various different topics. It was a great success, and everybody was just extremely happy.

The next cataclysmic event was the Russian invasion of Ukraine. Because this happened in 2022, and the International Congress of Mathematicians (ICM) was due to be held in St. Petersburg in the summer. So we had to decide what to do on the spot.

I had contemplated beforehand what we would do in this case, because I had a feeling it was going to happen. So I discussed the plan with the Secretary General of the IMU at 4 in the morning our time. We had a virtual meeting with the Executive Committee. Then we had the meeting, and one of the members of the Executive Committee was Russian. And he was a good friend of mine. And he was beside himself, so it was a very difficult meeting.

So I presented the plan, the Executive Committee approved it, we immediately wrote a statement from the Executive Committee, and then we were confronted with the fact that all the money for the meeting came from Russia. So we didn’t have access to it. And second, we had to reorganize the meeting with all the speakers, and we had to hire somebody to do an electronic version of the whole thing. The Secretary General had connections with a European foundation, and he secured some funding to be able to pay for everything.

We had to personally write to all the speakers to make sure that they were on board, that they understood how it was going to work, and so on. I had to chase many of them. And in the end, we got all but one. And this one is a very famous man who has layers and layers of protection — Yann LeCun — I couldn’t get through to him, the layers of people to get to him made it impossible. But every single other person was on board, on the order of 150 people.

As chair of the Fields Medal Committee, we had to select the members of the Fields Medal Committee. It had 12 members at the time. So that involves various considerations: field, country, gender, and all the standard things. And we formed an excellent committee.

We had a seminar over the summer before the final decision in which one member of the committee would make a presentation on the work of each of the finalists. Some of the most impressive contributions. So we had a very serious methodology. And of course, we wrote to hundreds and hundreds of people, got hundreds of opinions on each one of these candidates. And after that, we narrowed it down through our own discussions. And finally, we had the seminar. And then after the seminar, we had a further discussion. And then we had the final vote.

MM: I am very curious to hear whether you are, or were ever, interested in physics — for example, the applications of functional analysis (Hilbert spaces) to quantum physics.

CK: So I am sort of in principle, as an outsider, interested, but I don’t have the technical knowledge to actually be able to do anything about that.

MM: I am very curious to hear your thoughts on how AI can accelerate or influence math research.

CK: This is a big topic right now, not just in math. In general, what would the effect of AI be? Would it even be safe?

This is a very difficult topic, from being incredibly useful to potentially dangerous for the world. In mathematics, as far as I can tell so far, it is a useful tool for some things. But what hasn’t been seen to happen, as far as I know, is for AI to create an entirely new idea. This we haven’t seen. On the other hand, there are sometimes computations that are too large for humans. So, this certainly looks like a great tool. It also looks like it could be very dangerous. So, it is something we have to watch and look at. But the genie is out of the bottle; nobody can put it back. It is there.

What I hate is what it is doing to education. It is pointless to assign homework. Not pointless to assign it, but pointless to grade it. Because all of you guys are using AI to solve the problems. And this is extremely short-sighted. Because it means you don’t learn how to reason by yourself. And the students who are doing this are hurting themselves incredibly. They will be in trouble. It is a danger to the entire education system.

MM: Are you familiar with the book Gödel, Escher, Bach? It is my favourite book.

CK: I only have a vague impression of the book. But it seemed like something very interesting and very much fun. I think the analogy between art and math is a true analogy. It is an interesting thing to uncover.

In math, I know when I find something beautiful, and when I find something ugly, I also know it. But I don’t have any kind of scheme that I can use to explain it. I would say it is more visceral to me. I don’t analyze that kind of thing. But there are certain things that attract me.

MM: I would love to hear about your personal interests or hobbies, or do you have favourite books, favourite movies?

CK: I have many. There’s not a time when I don’t read. I read a lot of books. I love the opera when it comes to music. I don’t know how to sing. I never played an instrument, but my daughters have a lot of talent. They play the flute, they play the piano. But I enjoy the arts very much.

I liked, growing up, the short stories of Jorge Luis Borges. I have a personal experience with him because when I graduated from high school, I got some kind of prize for a math contest, and he handed it to me. And he and my advisor Calderón knew each other.

Nowadays, I tend to read a lot of mysteries. Right now, I’m reading a series of mysteries by a Cuban author whose last name is Padura. My friend, Gustavo, always gives me these books. He enjoys them, so he sends them to me.

When I was a kid, I read Jules Verne, Agatha Christie. Lots of books.

In 2022, I helped Vivek Mashrani with his book You Can Compound — originally self-published, it became a national bestseller in India, and was then re-published by Penguin — and I realised that the book publishing industry is ripe for disruption.

The sheer inefficiency in the process — long turnaround times, debates over inelegant designs, timeline negotiations — combined with the fact that leading publishing houses pay authors only ~10% royalty, presented a screaming opportunity for someone to start an unconventional book publishing company.

My conversations with author Jimmy Soni, founder of OSV Jim O’Shaughnessy, designer of the eudaimonia machine David Dewane, and director of UChicago Press Garrett Kiely, each corroborated this intuition.

All of this crystallised what I think a great publishing house looks like:

1. Author-first, both economically (higher royalty %) and philosophically (focused on enabling authors to produce their best work). When all the insights in the book are the author’s, why should they get only 10% of the economic value? Robert Pirsig’s Zen and the Art of Motorcycle Maintenance was rejected by 121 publishers: the traditional system nearly killed one of the greatest books of the 20th century.

2. Has good taste, meaning it is selective and only publishes high-quality books. Now obviously these are subjective notions. But in practice this means that for a certain group of readers, the phenomenon of ‘I will read any book Sebastian Mallaby writes’ extends to ‘I will read any book Stripe Press produces’. As a reader, you trust the taste of not just a specific author, but the publishing company as a whole. The current paradigm of readers having ‘favourite authors’ transforms into readers having ‘favourite book publishers’.

3. Crafts an immersive reading experience. This could mean high-quality printing, aesthetic fonts and cover designs, and even digital companions to the physical book. For example, this version of the Bhagavad Gita has a speaker pen that orates verses while reading them. Hannu Rajaniemi speaks about neurofiction, stories that change depending on the reader. And Tyler Cowen has written this AI-native book about the marginal revolution in economics.

I’m thrilled to see many smart people catching onto this opportunity. In this article, I highlight some of the new-age, unconventional publishers that I’m most excited about. These companies range from well-established with dozens of books published to newly-started with a couple of books announced, but each represents a distinct bet on what publishing can become.

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Stripe Press

Perhaps one of the first to catch onto this opportunity (?), Stripe Press has helped popularise books like Where Is My Flying Car? and The Art of Doing Science and Engineering, and bring to life books like The Scaling Era by Dwarkesh Patel. Their books also have really cool ‘living covers’ online.

Having said that, I’m not exactly a fan of the Stripe Press version of Poor Charlie’s Almanack — I prefer the blue-cover version for its numerous aesthetically-pleasing illustrations, which make a world of a difference to the reading experience.

Quanta Books

As a math and physics buff, I love reading Quanta Magazine, and it’s so exciting to see their upcoming books The Proof in the Code (about the math proof verification software Lean), Six Math Essentials (written by the legendary mathematician Terence Tao), and Everything is Fields (a book about quantum field theory from one of its most passionate communicators, David Tong).

I imagine I will read every book that Quanta Books produces…

Infinite Books

Founded by Jim O’Shaughnessy and headed by Jimmy Soni, one of my favourite authors. I loved his books A Mind At Play (biography of Claude Shannon) and The Founders (founding story of PayPal). An author who has gone through the traditional publishing process can bring deep nuance and insight into a publishing company, and Infinite Books is poised to benefit from his wisdom.

Their model treats the physical book as the anchor of a broader experience — their first book Two Thoughts came with an audiobook accessible only to buyers of the physical copy, an early example of what I think will become a growing trend towards digital companions for physical books. The book also came with a bunch of cool stickers!

Arena Books

From the creators of Arena Magazine. They have a coffee table book called Silicon coming out in May that I pre-ordered as soon as I heard about it. It’s “an art book and anthology” about the semiconductor revolution and looks stunning! Talk about good taste: this book has “a special foil stamped cover, a genuine thread binding, and 384 pages of European archival paper”, hundreds of full-page photographs, and essays by such insightful people as Dylan Patel.

Challenges

The biggest challenge I see for someone wanting to start a new-age publishing house is distribution. The existing publishers — HarperCollins, Random House etc. — are too embedded in conventional channels like bookstores.

I am yet to see a Stripe Press book at an airport bookstore. Publishing a book with Penguin almost guarantees a certain level of visibility, discovery and sales, and it is hard to see why any author would give that up voluntarily.

Online channels, particularly social media and online newsletters/podcasts, seem to be the most plausible solution to the distribution problem for these new-age publishing houses. Quanta and Arena each have magazines with thousands of readers they can cross-sell their books to (so does Stripe, with Works in Progress). Jim O’Shaughnessy, Jimmy Soni and Dylan O’Sullivan have strong personal brands and a substantial social media follower base to drive sales for Infinite Books. If done well, the distribution problem can be solved.

It is also an open question whether it is possible for the publishing company to be profitable while giving authors a larger chunk of the royalties. My understanding of the unit economics is that currently, a large chunk of a book’s retail price goes to Amazon or the bookstore as their profit margin. Sidestepping this by constructing an alternative distribution pipeline can enable the publisher to provide a greater share of author royalties.

The other possible route is that a high-quality, devoted reader base — attracted by being tasteful — means you have pricing power. Arena’s Silicon book is priced at $99, for example.

The upshot of taking on these challenges is that we can break the shackles of the conventional publishing industry and create deeply meaningful, well-crafted books that are works of art. We can create the next generation of GEBs, Power Brokers, and Poor Charlie’s Almanacks that continue to inspire curious minds. Seeing this wave of new-age publishing companies makes me feel like a kid in a candy store — it’s an exciting time to be a bookworm!

Feedback and reading recommendations are invited at malhar.manek@gmail.com

AI for Math and Science Research

It seems to me that AI will tremendously accelerate math research. Math is a highly formal, verifiable system (like chess or Go, but with a much larger combinatorial search space) and seems perfect for RL to work its magic. So I would not be surprised if, by [insert-time-frame-depending-on-how-AGI-pilled-you-are], there is an order of magnitude increase in the number of new theorems proved per unit time. Some questions pertaining to this:

1. Suppose we get to the point where models run for long times (kind of like the computer in The Hitchhiker’s Guide to the Galaxy that runs for millions of years and outputs “42”) and prove new theorems in math — how valuable would this be, and in what way? Suppose an order of magnitude more theorems are proved per year than current levels. How exactly will this impact the world? Will it just be a vast collection of arcane, abstruse math theorems, or will some of them find applications in say physics or computer science?

2. Will the companies that create these AI-enabled-math-research-juggernauts even publish the most profound theorems, or keep them private? Will math research remain a collaborative endeavour (as it is today, with human mathematicians who publish their results for others to build upon) or become a competitive one?

Note: I really enjoyed reading this vision by Math Inc.

Deep Tech and Manufacturing

1. From a first-principles standpoint, multi-junction solar cells seem like the obvious successor to monoPERC and TOPCon for breaking past the Shockley-Queisser limit on the efficiency of a single-layer solar cell (~33%). Yet they remain a niche, space-only technology. Why is this? Why aren’t multi-junction solar cells, which have far greater efficiency, more widely produced and used?

2. If every computational task reducible to an unstructured search or optimization problem becomes quadratically faster (Grover’s algorithm in quantum computing), what are the economic effects? Forget implementation of Shor’s which would create whole new categories of value, just sqrt(n) speed up by Grover’s algo would sharply reduce logistics and supply chain costs for physical manufactured goods, causing a deflationary supply shock: what are the percolation effects of this in the economy? How much would GDP be impacted by a square-root speedup in every relevant algorithm?

Intelligence and Espionage

1. In his essay series on Situational Awareness, Leopold Aschenbrenner writes:

   There’s a lot of low-hanging fruit on security at AI labs. Merely adopting best practices from, say, secretive hedge funds or Google-customer-data-level security, would put us in a much better position with respect to ‘regular’ economic espionage from the CCP. Indeed, there are notable examples of private sector firms doing remarkably well at preserving secrets. Take quantitative trading firms (the Jane Streets of the world) for example. A number of people have told me that in an hour of conversation they could relay enough information to a competitor such that their firm’s alpha would go to ~zero — similar to how many key AI algorithmic secrets could be relayed in a short conversation — and yet these firms manage to keep these secrets and retain their edge.

How do private intelligence networks work, from quant hedge funds to big tech? (Any good reading material on private intelligence/corporate espionage - blogs, books, papers, etc.?)

2. It seems like a lot of China’s technology sector — from solar to EVs to batteries — has been built off of US technology. What is the nature of this techno-industrial espionage? How does it work?

3. The textbook Quantum Computation and Quantum Information by Michael Nielsen and Isaac Chuang says:

   Rather remarkably, public key cryptography did not achieve widespread use until the mid-1970s, when it was proposed independently by Whitfield Diffie and Martin Hellman, and by Ralph Merkle, revolutionizing the field of cryptography. A little later, Ronald Rivest, Adi Shamir, and Leonard Adleman developed the RSA cryptosystem, which at the time of writing is the most widely deployed public key cryptosystem, believed to offer a fine balance of security and practical usability. In 1997 it was disclosed that these ideas — public key cryptography, the Diffie–Hellman and RSA cryptosystems — were actually invented in the late 1960s and early 1970s by researchers working at the British intelligence agency GCHQ.

   And Michael Nielsen also writes in his essay Quantum computing for the very curious:

   This ability to break encryption has made the world’s intelligence agencies very interested in factoring, and they’ve poured enormous sums of money into quantum computing research since the mid-1990s. Indeed, there’s a good (as yet unwritten) history book to be written about how the rise of quantum computing was caused by the interest of the world’s intelligence agencies in accessing humanity’s private thoughts.

   This is another example of why I find myself fascinated by intelligence agencies and their workings. What are some other technological innovations that intelligence agencies pioneered but kept classified? I would love to read the book that Nielsen calls “as yet unwritten”!

4. What exactly is open source intelligence? Best resources to learn more about it?

Miscellaneous

1. There is this interesting bit about Srinivasa Ramanujan and G. H. Hardy in Gödel, Escher, Bach. Hardy writes:

   I remember once going to see him [Ramanujan] when he was lying ill at Putney. I had ridden in taxi-cab No. 1729, and remarked that the number seemed to me rather a dull one, and that I hoped it was not an unfavorable omen. “No,” he replied, “it is a very interesting number; it is the smallest number expressible as a sum of two cubes in two different ways.” I asked him, naturally, whether he knew the answer to the corresponding problem for fourth powers; and he replied, after a moment’s thought, that he could see no obvious example, and thought that the first such number must be very large.

   Then Douglas Hofstadter goes on to write:

   It turns out that the answer for fourth powers is: 635318657 = 134 + 1334 = 1584 + 594. The reader may find it interesting to tackle the analogous problem for squares, which is much easier.

   It is actually quite interesting to ponder why it is that Hardy immediately jumped to fourth powers. After all, there are several other reasonably natural generalizations of the equation u^3 + v^3 = x^3 + y^3 along different dimensions.

   For instance, there is the question about representing a number in three distinct ways as a sum of two cubes: r^3 + s^3 = u^3 + v^3 = x^3 + y^3.

   Or, one can use three different cubes: u^3 + v^3 + w^3 = x^3 + y^3 + z^3.

   Or one can even make a Grand Generalization in all dimensions at once: r^4 + s^4 + t^4 = u^4 + v^4 + w^4 = x^4 + y^4 + z^4.

   There is a sense, however, in which Hardy’s generalization is “the most mathematician-like.” Could this sense of mathematical esthetics ever be programmed?

   My question is, why does Hofstadter believe that Hardy’s generalization is “the most mathematician-like”? What makes him think this?

2. What does the future of reading and writing look like in a world with AGI? Is reading and writing books valuable? Will the future Dostoevsky’s and Kafka’s be humans or AIs (or both?) Will the legendary books of the future — the GEBs, the LoTRs — be written by humans or AIs (or both?)

3. There are these ‘trilemmas’ (three-sided dilemma problems) that show up in many fields. For example, interest rates, exchange rates and inflation in monetary theory: you can choose to control any 2 out of the 3, and the third will be a consequence. Similarly, the CAP theorem in data science says that a distributed data store can simultaneously provide only 2 out of the following 3 guarantees: consistency, availability and partition tolerance. There is also the bandwidth-error-power trade-off in information theory. Is this genre of trilemma theorems simply an interesting coincidence or is there more to it (e.g., does it imply something about the dimensionality of our world/the ‘Fabric of Reality’?)

4. What if we take the multiverse seriously? What would be some non-trivial implications of subscribing to the multiverse interpretation?

Other People’s Questions

I also want to echo some questions that other people have posed, that I find interesting to think about.

1. Dwarkesh Patel asks -

   What real world impact should we expect from the current batch of AI for math projects? What are the fields of technology where people are going, “Ah we could totally solve quantum computing (or fusion or AGI) only if we had more theorems!” But maybe problems in biology and physics and materials and so on reduce down to math in a way I’m not foreseeing, and automating formal math alone is enough to unlock a bunch of progress.

2. Luke Gromen asks -

   A macro question that is not being asked yet:
   
   “How much were gold prices capped historically by the expansion of credit (unallocated paper) gold?”
   
   Many opining on the gold/oil ratio (GoR), but few seem to be asking if GoR would've been far higher had credit gold not capped GoR.

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MM: You graduated with a First Class degree in modern history from Oxford — what was that experience like? What were your favourite classes, favourite professors, favourite tutorials?

SM: Oxford gave students a broad choice in what they focused on. My concentration was British and European history from around the mid 1850s to 1939. Of course, the main political drama in that period was the contest between socialism, democratic capitalism, and fascism. I became fascinated by the question of why the left was a big factor in France, Germany, Italy, Spain and obviously Russia. But Britain had no Marxist movement to speak of. The reason lay in the malleability of the British establishment. By gradually extending the franchise and offering some measure of economic inclusion, Britain turned the revolutionary left into the pragmatic, labor union left. Pragmatism bred pragmatism, in other words. It’s a lesson we might recall today in these polarized times.

MM: From my observations it seems like the species of macro hedge funds (once thriving with George Soros, Jim Rogers, Paul Tudor Jones etc.) has gone extinct or at least endangered in recent times. For example, Peter Thiel’s Clarium Capital suffered losses post 2008 and was shut down; Ray Dalio’s Bridgewater has underperformed the S&P. Why do you think this happened? Can it be revived — if so, how?

SM: Macro hedge funds grew up in response to the end of the dollar-gold peg in 1971, which caused currency fluctuations that could be traded. Macro trading then entered its prime in the 1990s, when governments tried to tame currency volatility by soft-pegging their currencies. The soft pegs set up easy targets for hedge funds, which could sell so much of a weak currency that the pegs would eventually break, handing the traders a fortune. Breaking a soft peg was how Soros and other macro traders profited from the devaluation of the British pound in 1992, and versions on the same drama played out in Asia later in the decade. These days macro trading is somewhat subdued, because there are fewer ill-considered currency pegs to target. Most currencies float, and the ones that don’t (e.g., in East Asia) are generally being artificially held down rather than being propped up. When a currency is being held down, it does not present a target for speculators because the government can always print and sell more of its own currency to keep it down. This is the main reason that macro funds are less successful these days, though there are still opportunities to trade currencies, interest rates and so forth.

MM: What do you think about the species of philosopher-investors? George Soros comes to mind for his theory of reflexivity. Similarly, Peter Thiel for his synthesis of Girardian and Straussian ideas into his investing. How do such people operate? Is their philosophy an attempt to intellectualize or is it deeply intertwined with their investing? And what do you think about being a philosopher-investor in the age of AI?

SM: Hedge fund investing is a highly intellectual pursuit, so not surprisingly many practitioners are also interested in philosophy. In the special case of George Soros, the theory of reflexivity opened his mind to the boom-bust nature of financial markets: reflexivity’s insight is that opinions of what will happen can be self-fulfilling, and that the feedback loop between belief and reality can drive a market so far from fair value that it will eventually reverse violently. But in general I would doubt that the philosophy of hedge fund investors has a lot to do with how they actually trade.

MM: Renaissance Technologies hires the best and brightest PhDs in physics, math, astrophysics and computer science. Evidently, they have done extremely well at generating returns as a quant hedge fund — but what do you think about the societal cost of redirecting top scientific talent into finance (“brain drain”)?

SM: The diversion of scientific talent into quant trading often raises concerns, but I don’t think there is a strong case for worrying. I say this for six reasons.

    First, the hundred or so PhDs at Renaissance Technologies are extremely smart, but one hundred is a tiny number relative to the number of PhDs employed at a tech company. For example, Alphabet is thought to employ several thousand PhDs.

    Second, the hundred-strong team at Renaissance Technologies is eliminating inefficiencies in a very broad range of financial instruments—currencies, stocks, commodities—and they are doing this globally. So the world is getting a lot of additional efficiency from a relatively small number of quants. This efficiency ensures that average retail investors can sell their positions any time without worrying that they are selling at a bad moment when some sort of liquidity distortion or other temporary dislocation will cause them to be ripped off. It’s hard to quantify the social benefit of this financial efficiency, but it’s non-zero. We don’t really know whether those same hundred PhDs would have contributed more to society by staying in academia or going into other industries. But we can’t be sure that their contribution would be greater.

    Third, the discussion of where or how quants contribute most assumes that there is a fixed number of quants. But the rise of quantitative trading creates an incentive for young students to get a quantitative training. The success of Renaissance Technologies has probably increased the supply of Americans doing graduate degrees in fields such as math, computer science, or physics. So, a bit like the famous “lump of labor” fallacy in economics, there is a “lump of quant” fallacy in this debate.

    Fourth, Jim Simons, the founder of Renaissance Technologies, created various philanthropic initiatives to fund math education and scientific research. When my daughter did an astrophysics PhD at UChicago, the Simons Foundation was funding a lot of the activity in her field. (She had no idea that this Simons was the same person as the founder of the hedge fund that I had written about.) Likewise, DE Shaw, founder of the eponymous quant hedge fund, also created DE Shaw Research, creating research jobs for several dozen PhD scientists. A Shaw Research alum, John Jumper, won the Nobel Prize in 2024.

    Fifth, free societies should allow quants to choose for themselves where they want to work. If we start second-guessing their choices, we could second-guess a lot of other ones. Should we allow people to work in the fashion industry, which labors to extract large sums of money from clothing whose functional value is indistinguishable from cheaper clothing? Isn’t the fashion industry stoking envy and insecurity? Shouldn’t we require smart business leaders to work in other fields? (Obviously not!)

    Finally, and more generally, it’s often argued that the growth of employment in the financial sector is a disturbing trend. Do we really need all these spreadsheet jockeys? But as economies become more technically specialized and complex, it’s reasonable for the financial sector to grow, because the role of finance is to allocate capital wisely to all these technical and specialized industries. We know from experience that central planning is a bad way to make these allocation decisions. So we need a sophisticated financial system to do it.

MM: With the proliferation of VC funds, it seems like capital is becoming a commodity. What really differentiates one VC shop versus another? Is it track record? Value added to investee companies? What are some examples of real differentiation?

SM: Track record certainly helps. Most founders would be happy to take money from one of the top funds because the brand is valuable: saying “I’m doing a startup” will elicit a shrug, but saying “I’m doing a startup backed by Sequoia” confers instant credibility. But VC partnerships also get into deals because a particular partner has a good reputation. A strong VC partner may add value to a startup by bringing engineering judgment, hiring experience, go-to-market skills, introductions to potential customers, a network in another country, or even just emotional solidarity and counselling. Also, there are many stories in venture about startups that get turned down by famous VCs, eventually take money from a non-famous one, and then do well—PayPal was initially backed by Nokia Ventures for example. So it’s not just deal access that matters in venture. Deal selection is another differentiator.

MM: From Napoleon Ta of Founders Fund to the team at Renaissance Technologies, some of the best investors prefer to stay under the radar. When you start a new book, what exactly helps you get access — emails sent, mutual friends tapped, documents requested? A concrete walk‑through would be invaluable to aspiring long‑form writers.

SM: It’s all of the above. You have to try everything and eventually you may get access. Expect to have the door slammed in your face a few times. But in general it’s a combination of getting to know people who know other people who then eventually intro you to the people you need to interview, and being very well prepared at each step of the way. Don’t expect people to spend time with you if you haven’t studied all that’s public about them already. When I go see someone, I often have ten pages of typed questions that I’ve worked on for days. If I’ve put in the time, the interviewee is more likely to put in the time. If I can complete their sentences for them because they are repeating a point they have already made on a podcast, this will encourage them to dig deeper and say something surprising that they have not aired with any other writer.

MM: What are the most fascinating use cases of AI in investing that you have seen, across all stages from VC to public markets?

SM: I actually think that being a venture capitalist is one of the jobs that is least likely to be disrupted by AI. Being a VC is about bonding with human founders. It is about judging whether a brand-new product idea will be of interest to human customers. It is about imagining the future—and the future is not in an AI’s training set. On the other hand, there are other types of investing that have been using AI for quite a while—algorithmic market making and so forth. Between these two poles, there are funds that haven’t historically used AI but that are now starting to do so. I hear of lots of use cases: for example, a merger-arb hedge fund that can ask an LLM for help analyzing how an anti-trust review is likely to come out.

MM: What are 3 books you would love to read that nobody has written? What are 3 books you most highly recommend reading?

SM: I’m fascinated about how, in common law systems, private lawyers can invent novel legal structures that change the way that capitalism functions; and yet they are anonymous, have no democratic mandate, and most people don’t even realize that the rules are created this way. So I think a great book on the industry of commercial law would be worthwhile. It’s grown like crazy in New York and London. It’s powerful. It’s secretive. What more do you want? (It would be a huge task to gain access!)

Good books to read: I loved The Money Game by Adam Smith, an old classic about the market frenzy of the 1960s. I also thought Too Big To Fail by Andrew Sorkin, a fly-on-the-wall account of the 2008 financial crash, was wonderful. I am looking forward to reading Sorkin’s new book on the 1929 crash.

MM: What book are you working on next?

SM: By luck, I negotiated deep access to DeepMind, the Google AI lab, in November 2022—the same month that ChatGPT turned AI into a cultural obsession. Since then, I’ve interviewed around a hundred AI scientists inside and outside the lab, and spent more than thirty hours with Demis Hassabis, DeepMind’s principal founder. Hassabis is an extraordinary character, and AI raises profound questions about the nature of human cognition, the future of human society, and the dilemma of the scientist who creates a potentially existential technology—what I think of as the “Oppenheimer conundrum.” Friends who have read early drafts of the manuscript tell me this is my best book so far—but then those are my friends! The book will be out in 2026.

Here is the transcript of our email exchange.

MM: In Cryptonomicon, Neal Stephenson writes - “As it happens, Alan has become fascinated by the incarnations of pure ideas in the physical world ... Turing is neither a mortal nor a god. He is Antaeus. That he bridges the mathematical and physical worlds is his strength and his weakness”. What, to your mind, are the most beautiful examples of the physical manifestations of a pure math idea?

CH: Computation in general is pretty cool, and widely underappreciated. Any computer can simulate any other computer is kind of mind boggling.

MM: From a first-principles standpoint, multi-junction solar cells seem like the obvious successor to monoPERC and TOPCon for breaking past the Shockley-Queisser limit. Yet they remain a niche, space-only technology. In your view, what is the single biggest physical or manufacturing bottleneck preventing their terrestrial dominance, and what non-obvious breakthroughs are needed to unlock a cost-competitive learning curve for them?

CH: I don’t know much about emerging PV technology. The biggest obstacle for PV in general is permitting reform. For perovskites and other more exotic PV technology, the roadmap is clear - get to positive unit economics and then ride a cost curve that is at least as steep as the incumbents.

MM: The 2023 Terraform white paper (version 2) says that synthetic fuel will use 80+% of all solar generation long term — this implies that in the long term, converting photons to molecules will outcompete storing electrons in batteries (and discharging when needed). Could you walk me through the reasoning for why you believe >80% of solar power will be used for DAC fuels and not to charge batteries for battery energy storage?

CH: The leading order term is that chemical synthesis is intrinsically inefficient, so that's a 3x boost right there.

MM: What is the first principles reason for why 1 MW solar module produces 6,500 cubic feet of CH4? In that chain from solar panels to electrolysis to the Sabatier reaction, what are the key bottlenecks that prevent an even greater throughput of CH4 per MW of solar generation?

CH: 1 MW solar array produces about 6 MWh per day (sun is underground half the time, and pointing in the wrong direction another half of the time). 6 MWh is equivalent, energetically, to about 20,000 cubic feet of CH4, but the synthesis process is not very efficient. First, most of the power goes to making H2, at perhaps 60% efficiency. Then half that hydrogen just gets converted into water instead of methane. But you get a little bit of efficiency back because the carbon atom that’s released to become CH4 from the O2 that becomes water, also has positive enthalpy of combustion. So all up, about 30-35% efficiency. There are known ways to push this into the high 40s, and physically 60% efficiency is probably possible - but it would not be close to cost optimal.

MM: There are several emerging trends in AI data centers - e.g., bitcoin mines being converted to AI data centers, direct liquid cooling to the chip, orbital/in-space data centers, modular/containerized data centers etc. Which of these (or any others) do you find most promising, and why?

CH: I think the most promising is direct DC HV systems, including racks powered in series. All the other stuff is either too exotic, or I’m not qualified to speculate, or both.

MM: In your podcast with Dwarkesh, you spoke about the potential for integrated solar with chips (power with compute), since both are fundamentally made of the same material — silicon — albeit at different purity levels. Could you paint a picture for what such an integrated solar-GPU might look like and how TSMC might build it?

CH: That’s a hypothetical about the distant future state of humanity. With our current manufacturing tech, the chips cannot be larger than the lithography field of view, which is too small. So let your imagination run wild.

MM: Like yourself, I am majoring in physics and math. What are the most profound and elegant concepts you learnt in college that fundamentally rewired your thinking? Could you convey that elegance and beauty to motivate why one must study them? (E.g., in freshman year I found Fourier transform and Tychonoff's theorem the most beautiful).

CH: Probably the earliest “aha!” moment I can remember was showing that central inverse square laws give rise to “orbits” broadly construed that map perfectly to the conics, which is to say projections of cones and planes. Something quite profound about that duality, and it provides a strong hint of similarly deep principles, such as holography, that I encountered later.

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On Writing

I’ve been writing this blog for ~2 years now — it’s helped me improve the quality of my writing, and I’ve met some fascinating people who reached out after reading something I’d written. If you’re intellectually curious and enjoy discussing ideas with other curious people, I would encourage you to write a blog.

The Ultimate Guide to Writing Online by David Perell. This is the essay that inspired me to start writing online. A comprehensive, detailed guide on why you should write online and how to do so. I’ve shared this piece with a few friends and I’m glad some of them have started their own blogs.

A blog post is a very long and complex search query to find fascinating people and make them route interesting stuff to your inbox by Henrik Karlsson. His thesis is that you should write stuff that you would love to read yourself. This is exactly my philosophy in writing this blog.

On Deep Tech

I’m very interested in all things deep tech — recently I’ve been thinking about AI, data centers, solar, and batteries.

Casey Handmer’s podcast with Dwarkesh Patel. They speak about all things solar and AI data centers. Towards the end, he suggests the possibility of integrating solar cells with chips (since both are made of silicon, simply of different purities).

A presentation by Andy Bechtolsheim about liquid cooling for AI data centers. He was the first angel investor in Google! This talk is extremely insight-dense. The future of cooling is immersion, not air.

A tweet by Sridhar Vembu about the importance of deep tech R&D in India. He explains why we need to develop indigenous technologies and how to do so in a long-term, sustainable manner. He is the founder of Zoho and a deep thinker; I always look forward to his tweets and interviews.

A tour of Ola’s lithium ion cell factory. It’s quite a complicated process with electrode winding, electrolyte filling etc. The entire factory is a clean room. This is a tour of CATL’s factory — a Chinese company with 37% global market share in batteries. One of the largest alongside BYD, Gotion and EVE — all Chinese companies! Just compare the two:

• Ola (India’s first cell factory) can make 0.1 to 0.2 million cells per day.

• CATL makes 2.2 million cells per day in just this one factory. And they have 13 factories globally.

Feedback and reading recommendations are invited at malhar.manek@gmail.com

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If you’re anything like me, you’re probably wondering What the hell is xAI up to? The key to understanding this, I think, emerges when we ask a very different question: What do poker players and pickpockets have in common?

For one thing, they both try to take other people’s money. But more interestingly, they prefer to act last. This is why poker players love being the dealer, who is last to act for every round post-flop. It is also why pickpockets are the last ones to get off when a train halts at a station.

Losing 200 euros to a pickpocket is an experience one can hardly forget. What I remember most vividly is that the thief got off the train after the doors had started closing. You know how they say ‘stand clear of the closing doors please’ and then you stand back as the doors shut? Except, this pickpocket didn’t — he exited after the doors had begun closing.

It’s actually very simple. If you leave while the doors are wide open, the victim can realise he’s been robbed and follow you. But if you exit in the nick of time, just before the doors close, then the victim has no choice but to say goodbye to his money.

It reminds me of what Peter Thiel — in his classic, contrarian style — calls last mover advantage, a flip on the typical business adage of first mover advantage. This excerpt from Zero To One explains it best.

The Last Will Be First

You’ve probably heard about “first mover advantage”: if you’re the first entrant into a market, you can capture significant market share while competitors scramble to get started. But moving first is a tactic, not a goal. What really matters is generating cash flows in the future, so being the first mover doesn’t do you any good if someone else comes along and unseats you. It’s much better to be the last mover — that is, to make the last great development in a specific market and enjoy years or even decades of monopoly profits. The way to do that is to dominate a small niche and scale up from there, toward your ambitious long-term vision. In this one particular at least, business is like chess. Grandmaster José Raúl Capablanca put it well: to succeed, “you must study the endgame before everything else.”

Thiel’s last mover concept is powerful, but what is the underlying physics? Across all these examples — from the poker table to the train platform — the advantage of acting last boils down to two key forces: information and commitment. The last mover wins because they act with the most complete information, while their final action creates an irreversible commitment that their opponents cannot counter. The poker player sees every bet before acting. The pickpocket acts at the precise moment when closing doors make it impossible to chase him. The last great development in a market creates a moat that competitors can’t cross. The advantage isn’t in the timing itself, but in how timing is weaponized.

Let’s look at how this works in poker. If you are first to act (under the gun), you can either bet and risk getting re-raised, or check and risk appearing like you have a weak hand. Either way, you are much better off being last to act (button/dealer), when you can see what everyone else has bet, and then choose to call, fold or raise. The last player has a big informational advantage.

The recent movie F1 dramatizes this principle perfectly. At one point, Sonny Hayes (protagonist, played by Brad Pitt) appears to have suffered a malfunction in his car, due to which he is still stuck on the starting grid, while other cars have already left for the formation lap. Turns out, there was nothing wrong with the car. It was a deliberate, strategic masterstroke by Hayes — by leaving last, his car had the warmest tires when the formation lap ended, since the other cars had halted so their tires cooled off. In this case, Hayes’ advantage stems not from information but from commitment — the other drivers have no way to warm up their tires instantly.

This principle of weaponizing the timing extends beyond high-stakes competition and into the crafts of persuasion and investing.

When legendary investor Rakesh Jhunjhunwala met Titan managing director Bhaskar Bhat for the first time, he requested the last meeting of the day, so that Bhat wouldn’t be in a rush to leave for another meeting, and they would be able to speak for longer.

Gyanvatsal Swami, the great motivational speaker, prefers to be the last speaker at any conference — this way, he can listen to all the other speakers before him, and mention their ideas in his own speech.

Which brings us back to xAI. Seen through the lens of the last mover, their recent surge isn’t surprising — it’s strategic. xAI wasn’t the first frontier LLM company from the US, but it may well be the last (alongside OpenAI, Google, Meta and Anthropic). By launching after the doors had started closing, they’ve not only caught up with the best models but also appear to be improving much faster than peers.

The lesson of the last mover advantage is not to be slow, but to be deliberate. It teaches us to see every decision not as a race to be first, but as a strategic chess match where the final move is often the only one that counts.

In your next project, poker game, or investment, ask yourself: How can I gather more information before I act? And how can I time my final move to create an irreversible advantage? Don’t just play the game — study the endgame.

Feedback and reading recommendations are invited at malhar.manek@gmail.com

Unless you have been living under a rock, you have probably heard of the PayPal Mafia. Early PayPal employees went on to start, lead, or invest in, Facebook, SpaceX, Tesla, YouTube, LinkedIn, Palantir, Uber, Lyft, Stripe, OpenAI, Airbnb, Sequoia Capital, Founders Fund, Neuralink, Yammer, Yelp, Quora, Reddit, Tumblr, Pinterest, Evernote, and Khosla Ventures.

In other words, PayPal Mafia = Bell Labs of the business world.

Interestingly, the only mention of the connection between Cryptonomicon and the PayPal Mafia I could find was the one sentence in Zero To One -

I don’t know of a single interview where any of the Mafia members mention the book (if you do, please email me!) So when I started reading it, I felt a dopamine surge like the one you get when you find a hidden intellectual treasure trove that the internet hasn’t discovered yet.

After pounding through the ~900 pages of intellectual fiction that is Cryptonomicon, from cryptography to information theory to business strategy and beyond, the things I’ve learnt are remarkable — by far the most insights I’ve gleaned from a fiction book. So here’s an essay about my top learnings, connecting the dots with the PayPal Mafia.

I think the first page of Cryptonomicon gives a great overview of what the book is about -

“There is a remarkably close parallel between the problems of the physicist and those of the cryptographer. The system on which a message is enciphered corresponds to the laws of the universe, the intercepted messages to the evidence available, the keys for a day or a message to important constants which have to be determined. The correspondence is very close, but the subject matter of cryptography is very easily dealt with by discrete machinery, physics not so easily.” —Alan Turing

This morning [Imelda Marcos] offered the latest in a series of explanations of the billions of dollars that she and her husband, who died in 1989, are believed to have stolen during his presidency. “It so coincided that Marcos had money,” she said. “After the Bretton Woods agreement he started buying gold from Fort Knox. Three thousand tons, then 4,000 tons. I have documents for these; 7,000 tons. Marcos was so smart. He had it all. It’s funny; America didn’t understand him.”

—The New York Times, Monday, 4 March, 1996

Let’s dive in!

Making License Plates

Cryptonomicon has 3 interweaved plot lines. One is about World War II military; another is about cryptography; and the third is about a startup. The startup, called Epiphyte Corporation, is run by Avi and Randy — an excerpt about this below, followed by some dot-connecting!

“Pinoy-grams?”

“Here’s how it works. You are an Overseas Contract Worker [in the Philippines]. Before you leave home for Saudi or Singapore or Seattle or wherever, you buy or rent a little gizmo from us. It’s about the size of a paperback book and encases a thimble-sized video camera, a tiny screen, and a lot of memory chips. The components come from all over the place — they are shipped to the free port at Subic and assembled in a Nipponese plant there. So they cost next to nothing. Anyway, you take this gizmo overseas with you. Whenever you feel like communicating with the folks at home, you turn it on, aim the camera at yourself and record a little video greeting card. It all goes onto the memory chips. It’s highly compressed. Then you plug the gizmo into a phone line and let it work its magic.”

“What’s the magic? It sends the video down the phone line?”

“Right.”

“Haven’t people being messing around with video phones for a long time?”

“The difference here is our software. We don’t try to send the video in real time — that’s too expensive. We store the data at central servers, then take advantage of lulls, when traffic is low through the undersea cables, and shoot the data down those cables when time can be had cheap. Eventually the data winds up at Epiphyte’s facility in Intramuros. From there we can use wireless technology to send the data to 24 Jam stores all over Metro Manila. The store just needs a little pie-plate dish on the roof, and a decoder and a regular VCR down behind the counter. The Pinoy-gram is recorded on a regular videotape. Then, when Mom comes in to buy eggs or Dad comes in to buy cigarettes, the storekeeper says, ‘Hey, you got a Pinoy-gram today,’ and hands them the videotape. They can take it home and get the latest news from their child overseas. When they’re done, they bring the videotape back to 24 Jam for reuse.”

…

“So, let me guess,” she says, “you are the guy doing the software.”

“Yeah,” he admits, a little defensive, “but the software is the only interesting part of this whole project. All the rest is making license plates.”

That wakes her up a little. “Making license plates?”

“It’s an expression that my business partner and I use,” Randy says. “With any job, there’s some creative work that needs to be done — new technology to be developed or whatever. Everything else — ninety-nine percent of it — is making deals, raising capital, going to meetings, marketing and sales. We call that stuff making license plates.”

She nods, looking out the window. Randy is on the verge of telling her that Pinoy-grams are nothing more than a way to create cash flow, so that they can move on to part two of the business plan. He is sure that this would elevate his stature beyond that of dull software boy. But Amy puffs sharply across the top of her coffee, like blowing out a candle, and says, “Okay. Thanks…”

Now, compare this to the memo Elon Musk wrote on August 2, 2006, titled “The Secret Tesla Motors Master Plan (just between you and me)”.

As you know, the initial product of Tesla Motors is a high performance electric sports car called the Tesla Roadster. However, some readers may not be aware of the fact that our long term plan is to build a wide range of models, including affordably priced family cars. This is because the overarching purpose of Tesla Motors (and the reason I am funding the company) is to help expedite the move from a mine-and-burn hydrocarbon economy towards a solar electric economy, which I believe to be the primary, but not exclusive, sustainable solution.

Critical to making that happen is an electric car without compromises, which is why the Tesla Roadster is designed to beat a gasoline sports car like a Porsche or Ferrari in a head to head showdown. Then, over and above that fact, it has twice the energy efficiency of a Prius. Even so, some may question whether this actually does any good for the world. Are we really in need of another high performance sports car? Will it actually make a difference to global carbon emissions?

Well, the answers are no and not much. However, that misses the point, unless you understand the secret master plan alluded to above. Almost any new technology initially has high unit cost before it can be optimized and this is no less true for electric cars. The strategy of Tesla is to enter at the high end of the market, where customers are prepared to pay a premium, and then drive down market as fast as possible to higher unit volume and lower prices with each successive model.

Without giving away too much, I can say that the second model will be a sporty four door family car at roughly half the $89k price point of the Tesla Roadster and the third model will be even more affordable. In keeping with a fast growing technology company, all free cash flow is plowed back into R&D to drive down the costs and bring the follow on products to market as fast as possible. When someone buys the Tesla Roadster sports car, they are actually helping pay for development of the low cost family car.

The way I think of this is, you start with a broad worldview and mission for what you want to accomplish (e.g., making humanity a space-faring civilisation), and then construct a business model around that vision. Who would’ve thought space exploration could be a business? Yet, SpaceX did it.

Start with a mission —> turn it into a business model to generate cash flows —> use the cash flows to expand in the direction of your larger mission —> repeat forever.

Here’s what writes about how Astro Mechanica is applying this idea.

When you want to fly somewhere – a little hop from SF to LA or a globe-spanning trip from New York to Tokyo – you book it directly with Astro Mechanica. You get there three times faster on planes designed and built by Astro Mechanica, powered by Astro Mechanica engines.

That’s the big goal, the one that changes the world by shrinking it.

But building planes that will fly passengers is a very expensive endeavor, thanks in part to the years and many test flights it takes to get a plane flight certified. A new Gulfstream might take 3 years and $5-7 billion dollars to get to the point at which it can start carrying passengers.

So you can’t start there. It would require so much venture capital that the founder wouldn’t end up owning anything at the end, even assuming he’s able to raise all the money. Plus, you’d want to run tests on something that you don’t mind blowing up.

So: to build the airline of the 21st Century, begin by launching rockets. Duh.

Space launch is the Roadster in Astro’s Tesla strategy: start at the highest end of the market and move cheaper and more mass market over time. From space launch to private planes (Model S), from private planes to commercial airliners (Model 3), building the airplane gigafactory along the way, until it’s churning out planes of all sizes cheaply and reliably.

And the below excerpt from Cryptonomicon reminded me of SpaceX’s reusable rockets.

If it will take ten years to make the machine with available technology, and only five years to make it with a new technology, and it will only take two years to invent the new technology, then you can do it in seven years by inventing the new technology first!

Philosophical Ways of Looking At Things

In the chapter titled Cycles, mathematicians Lawrence Waterhouse and Alan Turing are discussing an analogy between Turing’s bicycle and the German Enigma machine.

Waterhouse is thinking about cycles within cycles. He’s already made up his mind that human society is one of these cycles-within-cycles things* and now he’s trying to figure out whether it is like Turing’s bicycle (works fine for a while, then suddenly the chain falls off, hence the occasional world war) or like an Enigma machine (grinds away incomprehensibly for a long time, then suddenly the wheels line up like a slot machine and everything is made plain in some sort of global epiphany or, if you prefer, apocalypse) or just like a rotary airplane engine (runs and runs and runs; nothing special happens; it just makes a lot of noise).

*He has no hard data to back this up; it just seems like a cool idea.

Compare this to Peter Thiel’s standard question about college.

Is college a consumption good, like a four-year party? Is it an investment in the future? Is it an insurance policy? Or is it a tournament like the exclusive Studio 54 nightclub?

Contrarian Truths

To the savvy reader, Cryptonomicon is chockablock full of Thiel-esque contrarian truths and secrets. A couple excerpts below.

Dr. G. E. B. Kivistik had a few things to say about the Information Superhighway. He was a fiftyish Yale professor who had just flown in from someplace that had sounded really cool and impressive when he had gone out of his way to mention it several times. His name was Finnish, but he was British as only a non-British Anglophile could be. Ostensibly he was here to attend War as Text. Really he was there to recruit Charlene…

Another example, this time in the context of WW II cryptography, and its information theoretic implications.

“If what you are saying is true,” Lawrence says, “the jig must be up already. Rudy [the German cryptographer] must have figured out that we’ve broken their codes.”

“An informal system has been in place, which might be thought of as a precursor to Detachment 2701, or 2702 or whatever we are calling it,” Alan says. “When we want to sink a convoy, we send out an observation plane first. It is ostensibly an observation plane. Of course, to observe is not its real duty — we already know exactly where the convoy is. Its real duty is to be observed — that is, to fly close enough to the convoy that it will be noticed by the lookouts on the ships. The ships will then send out a radio message to the effect that they have been sighted by an Allied observation plane. Then, when we come round and sink them, the Germans will not find it suspicious — at least, not quite so monstrously suspicious that we knew exactly where to go. (emphasis added)

And one more.

The United States Military (Waterhouse has decided) is first and foremost an unfathomable network of typists and file clerks, secondarily a stupendous mechanism for moving stuff from one part of the world to another, and last and least a fighting organization.

Digital Currency

Gold-backed, cryptographically-enabled digital currency is perhaps the crux of the book. The parallels to Confinity — Peter Thiel and Max Levchin’s company that merged with X.com to become PayPal — are compelling.

Excerpt from the book -

“Doug. You can do this,” Randy says. “You get the gold. You put it on a boat. My friends here can explain the rest.” Randy fits the laptop’s plastic case back together and begins maneuvering the little screws back into their recesses.

Cantrell says, “You bring the boat here.”

Tom continues, “To that beach, right down the hill. I’ll be waiting for you with the Humvee.”

“And you and Tom can drive it downtown and deposit that bullion in the vaults of the Central Bank of Kinakuta.” Cantrell concludes.

Someone has finally said something that actually knocked Doug Shaftoe off balance. “And get what in return?” he asks suspiciously.

“Electronic cash from the Crypt. Anonymous. Untraceable. And untaxable.”

Compare this to what Jimmy Soni writes in The Founders, a book about the PayPal founding story -

In February 1999, Levchin attended the International Financial Cryptography Association conference. Hosted in Anguilla, a sliver of a Caribbean island, the annual gathering drew the leading players in academic cryptography and digital currencies. (To this day, Thiel, who attended the 2000 conference, harbors a theory that Satoshi Nakamoto—the mysterious founder of the cryptocurrency Bitcoin—was among the attendees.)

When Confinity had originally launched, it flirted with starting a universal digital currency free from government shackles.

In its original pitch documents, Confinity cast Mobile Wallet as a means of liberating the masses from currency-manipulating governments and reserve banks … Even the team’s casual internal parlance—“The World Domination Index,” for example, or the “New World Currency”—spoke to the aim of making PayPal a border-busting universal payments system.

X.com, too, had world conquest baked into its early DNA. One day, Musk hoped X.com would serve as the “global center for all money” and store the world’s dollars, deutschmarks (soon to be euros), and yen in one place. To Musk, this trajectory wasn’t revolutionary—it was obvious. Musk thought about currencies “from an information theory standpoint,” a reference to the field founded by Dr. Claude Shannon in 1948. “Money is an information system,” he explained. “Most people think money has power in and of itself. But actually, it’s really just an information system, so that we don’t have to engage in barter and that we can time-shift value in the form of loans and equity and stuff like that.”

Mathematical Skeleton

Two of my favourite excerpts from the book below.

The basic problem for Lawrence was that he was lazy. He had figured out that everything was much simpler if, like Superman with his X-ray vision, you just stared through the cosmetic distractions and saw the underlying mathematical skeleton. Once you found the math in a thing, you knew everything about it, and you could manipulate it to your heart's content with nothing more than a pencil and a napkin. He saw it in the curve of the silver bars on his glockenspiel, saw it in the catenary arch of a bridge and in the capacitor-studded drum of Atanasoff and Berry’s computing machine. Actually pounding on the glockenspiel, riveting the bridge together, or trying to figure out why the computing machine wasn't working were not as interesting to him.

As it happens, Alan has become fascinated by the incarnations of pure ideas in the physical world. The underlying math of the universe is like the light streaming in through the window. Alan is not satisfied with merely knowing that it streams in. He blows smoke into the air to make the light visible. He sits in meadows gazing at pine cones and flowers, tracing the mathematical patterns in their structure, and he dreams about electron winds blowing over the glowing filaments and screens of radio tubes, and, in their surges and eddies, capturing something of what is going on in his own brain. Turing is neither a mortal nor a god. He is Antaeus. That he bridges the mathematical and physical worlds is his strength and his weakness.

Investor Meetings

I found it fascinating how Avi prepares for an investor meeting.

Of the half-dozen important people in the room, three are middle-aged Filipino men. One of these is a high-ranking official in the PTA. The second is the president of an upstart telecommunications company called FiliTel, which is trying to compete against the traditional monopoly. The third is the vice president of a company called 24 Jam that runs about half of the convenience stores in the Philippines, as well as quite a few in Malaysia. Randy has trouble telling these men apart, but by watching them converse with Avi, and by using inductive logic, he is soon able to match business card with face.

The other three are easy: two Americans and one Nipponese, and one of the Americans is a woman … Her card identifies her as Mary Ann Carson, and claims that she is a V.P. with AVCLA, Asia Venture Capital Los Angeles, which Randy knows dimly as a Los Angeles-based firm that invests in Rapidly Developing Asian Economies. The American man … represents the Subic Bay Free Port. The Nipponese man is the executive vice president of a subsidiary of a ridiculously colossal consumer-electronics company.

Avi wastes little time in starting the videotape, which at the moment represents about seventy-five percent of Epiphyte Corp.’s assets. Avi had it produced by a hot multimedia startup in San Francisco, and the contract to produce it accounted for one hundred percent of the startup’s revenue this year…

It starts with footage — pilfered from a forgotten made-for-TV movie — of a Spanish galleon making headway through heavy seas. Superimpose title: SOUTH CHINA SEA—A.D. 1699. The soundtrack has been beefed up and Dolbyized from its original monaural version. It is quite impressive. (“Half of the investors in AVCLA are into yachting,” Avi explained.)

Cut to a stone tower on the crown of a green tropical island, where a lookout is sighting the (digitally inserted) galleon on the horizon. The lookout cups his hands around his mouth and bellows, in Spanish, “It is the galleon! Light the signal fire!” (“The family of the guy who runs the PTA is really into local history,” Avi said, “they run the Museum of the Philippines.”)

Cut to a series of shots of Manila townsfolk rushing to the seawall to adore the signal fire, including an Augustinian monk who clasps his rosary-strewn hands and bursts into clerical Latin on the spot (“the family that runs FiliTel endowed a chapel at Manila Cathedral”) as well as a clean-cut family of Chinese merchants unloading bales of silk from a junk (“24 Jam, the convenience store chain, is run by Chinese mestizos”).

A voiceover begins, deep and authoritative, English with a Filipino accent (“The actor is the brother of the godfather of the grandson of the man who runs the PTA”). Subtitles appear on the bottom of the screen in Tagalog (“the PTA people have a heavy political commitment to the native language”).

It reminds me of this extract from Walter Isaacson’s biography of Elon Musk.

For their first meeting with potential investors, [Kimbal and Elon] had to take a bus Sand Hill Road because the car their dad had given them broke down. But after word spread about the company, the VCs were asking to come to them. They bought a big frame for a computer rack and put one of their small computers inside, so that visitors would think they had a giant server. They named it “The Machine That Goes Ping,” after a Monty Python sketch. “Every time investors would come in, we showed them the tower,” Kimbal says, “and we would laugh because it made them think we were doing hardcore stuff.”

Haiku

Cryptonomicon starts with a haiku: a three-line poem with 5 syllables in the first, 7 in the second, then 5 again in the third. So, in that spirit, here’s a haiku I made up, to wrap up this essay.

Feedback and reading recommendations are invited at malhar.manek@gmail.com

Joe Rogan: When you look at the construction of the Great Pyramid of Giza, there’s 2.3 million stones in it. The whole thing points due north, south, east, west, it’s an incredible achievement. The stones, some of them were moved from a quarry 500 miles away, through the mountains. The biggest stones inside the king’s chamber weighed ~80 tons. It’s crazy, the whole thing’s crazy, like how did they do that?

Peter Thiel: I’m not sure I would anchor on the technological part, but I think the piece that is very hard for us to comprehend is, what motivated them culturally? Why did they do it?

Joe Rogan: Well, how did they do it physically? Why but also how. How is a big one, because it’s really difficult to solve. There’s no traditional conventional explanations for the construction, the movement of the stones, the amount of time it would take - if you moved 10 stones a day it would take 664 years to make one of those pyramids, so how many people were involved, how long did it take, how’d they get them there, how did they figure out how to do it, how come the shittier pyramids seem to be dated later?

Peter Thiel: I’ll trust you that it’s really hard, but I think the real mystery is why were they motivated? Because you can’t live in a pyramid, it’s just the afterlife of the pharaoh.

Joe Rogan: Well, there’s some debate around that … the old established theory in archaeology is that it was a tomb for the pharaoh, but new archaeologists are coming up with new theories…

Peter Thiel: I don’t know if this is an alternate history, but I’m always into the James Frazer, Golden Bough, Rene Girard, violence, sacred history...

Joe Rogan: That’s interesting but it still doesn’t solve the engineering puzzle. The engineering puzzle is the biggest one, like how did they do that?

Peter Thiel: What I’m focusing on is the motivational puzzle.

Joe Rogan: Yeah but if you have all the motivation in the world to build a structure that’s insane to build today, and you’re doing it 4,500 years ago, we’re dealing with a massive puzzle.

Peter Thiel: I think the motivational part is the harder one to solve. If you figure out the motivation, you’ll figure out a way to organise the whole society, and if you get the whole society working on it, you can probably do it.

The linguistic framing on this is that ‘can you do it?’ is subordinate to ‘do you want to do it?’ Whether or not you can do something matters only if you want to do it in the first place.

If you believe that ‘where there is a will there is a way’ (as a definite optimist would), then it becomes obvious that the important question to focus on — the constraint, the bottleneck — is not ‘what is the way?’ (engineering) but ‘what is your will?’ (motivation).

Motivating why we are learning or doing a certain thing is a piece that formal education often misses, I think. For example, physics courses on waves shove linear algebra down your throat — eigenvalues, eigenvectors, and that sort of thing. They teach you how to solve the characteristic equation

but why do we want to find the eigenvalues of a matrix? Why do we care about this equation in the first place? That’s what I asked my professor at office hours, and here’s what I discovered.

Suppose you have the differential equations

where x'' indicates the second derivative with respect to time. Note that x'' depends not only on x but also on y. We would like to decouple these equations, such that x'' depends only on x, and y'' depends only on y. This is the crux of the motivation. This is the why behind eigenvalues. Note that you can combine these equations to write, in matrix form,

Finding the eigenvalues allows you to re-write this as

thus decoupling the equations. This sort of explanation for the why, I think, is at least as important as learning how to compute the eigenvalues.

Motivation > engineering. Why > how. The contrarian version of Edison’s popular quote may well be 99% inspiration and 1% perspiration.

JOS: Even today, by the way, if you go to various financial sites or providers and look at the P/E for, say, Apple, what you’ll find is that if you go to Reuters, you’ll get one P/E. If you go to Compustat, you’ll get a different P/E. If you go to Bloomberg, you get a third P/E.

So one of the things that we undertook at O’Shaughnessy Asset Management that my team, I still think hasn’t forgiven me for was, a multi-year project of cleaning data. And that is kind of the blue collar version that quants are kinda like, wait a minute, I gotta spend my entire day figuring out what Apple’s actual P/E is? It’s garbage in, garbage out.

And I still marvel. I read academic papers. I don’t read them as much as I used to since launching the new company, but they’re just riddled with errors. I could put somebody on staff at OSV to simply write up all of the errors that that we find on a daily basis. And, of course, now we have our own in-house AI because the commercially available stuff, a lot of it is very highly nerfed, and we want the unvarnished version.

So we’re also building out an AI suite at OSV. We’ll be able to dump, for example, basically an unlimited number of papers into it and then look for all the errors. And I’m not a conspiracy guy, so I don’t think these errors were done intentionally. I think they were just done like humans. I mean, if you wanna find the weakest link in any system, it’s us humans.

So it’s a great aspiration to write a book as magical as Gödel, Escher, Bach. What would your theme be in the book?

[Context: one of my goals in life is to write a book that will be as magical to someone else as GEB was for me.]

MM: I’m still figuring that out. But I think it will certainly have a mathematical, rigorous component. It won’t be all right brain for sure, but it will also not be a textbook that is all left brain. It will be a balance of both.

I feel very often the ideas that I find very elegant are mathematically elegant results. For example, in my honors calculus class, it’s a proof based class. You don’t actually do calculus. It’s about proving the fundamentals of calculus. And one of the things we proved is that the real numbers are unique.

And I know that Gödel, Escher, Bach talks a lot about isomorphism, and we studied isomorphism in a slightly different meaning of the word, which is that, anytime you have 2 sets, if you have a 1-to-1 correspondence between those sets, that is called a bijection. And if the bijection is order-preserving, then it’s called an isomorphism.

The point being that if you have an order-preserving bijection, then for all effective purposes, the sets are exactly the same with the elements renamed. So, basically, the sets are exactly the same, except that you have called the elements different things.

We proved that if you have any set that has certain properties, like countable dense subset and connected, it has to be isomorphic to the real numbers. So in that sense, the real numbers are unique. And I thought that was a very, very elegant result. Even in physics, we did the first equation of Maxwell, which I thought was very elegant.

Even a much simpler thing like e^(iπ) = -1.

JOS: Yeah. That’s always a fun one.

MM: I also think it should have some artistic or creative component. One thing I’ve been thinking about is ‘intellectual fiction’. I think Neal Stephenson is a prime example. I think Cryptonomicon is clearly a standout example. It’s a fictional book, but it literally has math theorems and graphs and all these fascinating things.

JOS: You might like 2 books that I just finished. One is called The MANIAC, which is a fictionalised biography of John von Neumann. And it’s really enjoyable. I came late to that book, and I loved it. And then his first book, he’s a Chilean author, so these are the only 2 that are translated into English, something we hope to address with our book publishing arm, Infinite Books.

We’re hoping to be able to, in short order, simultaneously publish a book in all languages. It would be the electronic version, obviously, because that’s where it’s easy. But, the other book that he wrote that I finished just last week is When We Cease to Understand the World, and again, it’s also fictional and it’s looking at the various rivalries and various ways of trying to understand quantum physics and mechanics.

And it’s just so alive because he can take all the liberties he wants because it’s fiction. And yet it maps back to the actual history of the origins of quantum physics and Heisenberg and Schrodinger and how much they hated each other. These rivalries are a bit like Newton and Leibnitz, and it’s interesting how much they really informed what was going on.

And so it reminded me very much of what happened to poor David Bohm, who did the implicate and explicate order. Anyway, he was a student of Oppenheimer’s, and it came down during the McCarthy era that he was a communist or had communist sympathies. And so the way that these geniuses like Oppenheimer dealt with David Bohm is very much like the movie Mean Girls. Literally there was a thing that Oppenheimer wrote and said to his colleagues saying, “If we cannot disprove Bohm, then we must agree to ignore him.”

And that always fascinated me because people often forget, that, at least for now, a lot of this stuff is also informed by our very human emotions, likes, dislikes, etc. They affect even the purest math. And When We Cease to Understand the World really makes that point beautifully. And again, you couldn’t do it if it wasn’t fiction.

MM: I’m also a big fan of Claude Shannon, by the way. Like, huge, huge fan. I find it fascinating how he did all these different things. He was at Bell Labs, information theory, invested in the stock market, and made a killing on Teledyne and Motorola and all these great companies. I think he compounded at north of 25% CAGR for a couple of decades.

JOS: I love Shannon, and it still mystifies me that he is not more famous. Because, like, almost everything that we use on a daily basis needed Shannon to figure it out.

The Teledyne story is a really interesting one. Henry Singleton was an absolute genius at issuing shares to use as a cheap currency to acquire other companies, but then having the intuitive sense to know when he should buy them back.

I would bring Teledyne up in groups of asset managers, and and I’m talking big asset managers, right? And if I was sitting with 10 people, like, 8 of them had never studied Teledyne. I was always shocked by that.

So fictional version, but, also including mathematical formulas, beauties, etc. Interesting. And what would be the art part that you would bring in?

MM: I’m trying to figure it out. So maybe language and writing and that sort of thing, maybe photography. Could be astrophotography.

JOS: Oh, very cool. My wife is a street photographer and has a published book, and we collect art, and so I would say probably 30% of our collection is photography, 70% oil, sculpture, that kind of stuff.

But I’ve always enjoyed doing the rounds of the various photography exhibits with my wife because I ask her, why is this photograph so appealing? What about it is inviting me to be interested in it and commanding my attention? And I always figure there’s got to be a mathematical formula underneath it, and that is not always the case, but it is often the case.

It’s like in literature, the well known hero’s journey. Joseph Campbell was the first to really outline the actual step-by-step process of the hero’s journey. One of the things we’re programming our AI lab to do, is to be able to put a manuscript in it and rate it against the various underlying story structures.

One of our fellows is an architect, but he’s building an architecture for written works. And we think that’s really a fruitful endeavor, in terms of looking for kind of the pattern underlying why are some stories absolutely devoured by all of humankind, and others are just ignored? And what you do see is the underlying story structures give you a much greater insight into if you’re in the business of being a publisher and, you know, it’s a for-profit company.

That might be a very helpful piece of software for us to have, in terms of deciding whether we’re gonna go with this one book or one author over another.

MM: That brings me to something I wanted to touch on. I’m a voracious reader, but also I helped 2 authors with their books, and my name is in the acknowledgments of both. They are both bestsellers.

One thing that I had observed since then and, I had written in my notes, thought a lot about this, is that, I think there is a huge opportunity for a publisher that really changes the model. When I saw the process of creating these books, and I saw the whole journey very closely, I found it very dissatisfactory and inefficient. Penguin gives the author 10%. And I just felt it is a very, very inefficient process.

I think there’s a huge scope for a publisher that replicates the brand and distribution of say Penguin, has a quality filter, and does 80% royalty to author, 20% to publisher. And I know you do something similar at 70% to author, 30% for Infinite Books, which is basically the same. And so I want to dig in more and get your insights on that.

JOS: Listening to what you just said, that’s basically the goal of Infinite Books. Having written 4 books myself, I was very dissatisfied with the publishers. I had a variety of publishers. I had McGraw Hill, Broadway, and then yet another publisher. And in every case, it didn’t matter. It literally didn’t matter who the publishing company was. They all treated me the same. All of the line edits that they made actually detracted from the idea I was trying to express rather than amplifying it.

And so, when we launched Infinite Books, it was as a redress to everything that I and our editor in chief, Jimmy Soni, had really despised about publishers. Many books in America are still decided by people who hear something at a Manhattan cocktail party. If you wrote a great book right now and you submit it to the big publishers of the United States, the probabilities are very, very high that they you’ll get a rejection letter.

Whereas at Infinite Books we’re building tools that build in all of our quality filters into AI. So rather than it ending up in what traditional publishers call a slush file, we put every manuscript through the AI with the quality filters and everything.

And let’s say we get a thousand manuscripts — at a traditional publisher, they end up in that slush pile, and they have sometimes junior editors or readers who are meant to go through all of the manuscripts or the outlines, but it’s an incredibly laborious process, and they don’t do it well. And so, if you submit it to Penguin and all of the big publishers, Simon and Schuster, you’d probably get rejected.

If your book was really good and you submitted that manuscript to Infinite Books, we’d probably publish it if it passed all of our quality filters and everything else. But what we’re also trying to do is build a publishing company that is incredibly author friendly.

I joke that the big publishers in America, are using best practices, but only from 1925, not from 2025. If you were sitting at the top of Simon and Schuster and you had a huge back catalog — by the way, that’s where they make a lot of their money — and you were taking 90% of it and the author was getting 10%, or if it’s a really well known author, 15% of the royalties — are you gonna try to innovate that and do a 70, 30 split? I don’t think you are.

And that’s the challenge that we see with all of the traditional publishers. Large organizations tend to be very static and kind of set in their ways. So even if Simon and Schuster said it was gonna do a Skunk Works, side project to to use all the tools that we’re using at Infinite Books, I suspect that it would take them years and years and years and it would be so watered down because of the multiple committees it would have to go through.

And so a business model that is free from all of the constraints of the legacy companies can often break through. We did it with OSAM, for example. We sold O’Shaughnessy Asset Management to Franklin Templeton in 2021 because we had created this idea of custom portfolio creation, custom indexing, custom everything. And classic example, they saw that customization was the future, but they couldn’t build it internally because of all of their legacy issues. There’s a lot of psychological reasons why it doesn’t happen, a lot of human OS reasons why it doesn’t happen, but it’s applicable to other industries as well.

So what happens is a much smaller entity that has the right vision, and they do not have the bottlenecks of committees and other vicious things that stop innovation often dead in its tracks — then the big company simply watches, looks at all of the players in the field, and tags the one that they think is the best and acquire them. And that’s what happened to us.

If you get a bid like we did from Franklin Templeton that was at a price to magic ratio, you end up taking it. And so that gives us a a double interesting thing with Infinite Books and the other verticals that we’re building at OSV is, first off, we're doing it because I love books. I love authors. I love readers.

And it is a category that is ripe for disintermediation, ripe for arbitraging all of the inefficiencies out of it. So in either case, we think we’re gonna have a lot of fun, but also give voice to authors who have traditionally been ignored for a variety of reasons by the publisher.

MM: You mentioned Jimmy Soni, by the way. And I have interviewed him and Rory Sutherland for my Substack.

JOS: What did you take away from your interview with Jimmy?

MM: He mentioned a few stories about PayPal, and, like, the simultaneous chess game. And he said that many of the best founders are, intense game players. He said Travis Kalanick of Uber was the world’s top Wii tennis player. And these people just go very intensely into whatever they’re into.

I think he has spoken about this model of writing upwards versus writing downwards. And writing downwards is you’re an expert in the field, you are kind of writing down to the reader from up there. Versus writing upwards is like, I am very curious about this topic, and I am no expert in it, but I am very curious to learn more. And on that journey of curiosity-driven learning, patching things together, and presenting it to the reader. And I think he does that very well.

JOS: And the reason I made him editor-in-chief and CEO of Infinite Books was that very reason, but also he’s probably the most entrepreneurial author I’ve ever met, in that he really loves business. He really loves business models, all of those types of things. So I think he’s gonna be great in that spot at Infinite Books. And Rory Sutherland is on my advisory council. What did you get from Rory?

MM: He’s a gem of a guy. He always has the most unique insights. He said you can you can use 2 dishwashers, and you don’t need any storage for plates. The level of creativity that he has is unbelievable.

JOS: Did he tell you the story about how he solved British Airways’ big problem with all the complaints they were getting when they would text their passengers that a flight was delayed?

So his company was brought in by British Airways, and they were gonna assign a fairly large mandate to his company to help them reduce the amount of irate customers, from the delays that they were getting on flights. And Rory said, can you show me what you send? Like, if BA flight 10 is delayed, will you show me what you send?

And they said, we send a text and an email saying, BA flight 10 is delayed. Right? And he goes, I can solve your problem for you right now.

And they’re like, what? And he goes, just add by how long, the estimate, how long it's gonna be delayed. And he goes, it isn’t the fact that the flight is delayed that annoys your passengers. It’s the uncertainty about what they can do with the time that they actually have to spend waiting for the flight to take off.

And he said, so if a flight is delayed 20 minutes, they’ll be, oh, it’s only delayed 20 minutes. That’s not a problem. But if a flight is delayed 2 hours, they’ll say, I guess I can have go and have lunch and maybe do a bit of shopping and then return to the gate. And so they tried it and the volume of their complaints just shrank dramatically.

And then another one, when I was chatting with him one time, he just kind of abruptly said to me, why is Uber so successful? And I gave the kind of standard asset management answers for that. And he’s like, no.

Because people can see exactly where the car is, they’re good. They’re fine. It doesn’t matter if it’s a 12 minute wait time or a 2 minute wait time. As long as they can look at that little graphic of the car coming to them, they’re absolutely fine.

Feedback and reading recommendations are invited at malhar.manek@gmail.com

MM: I want to begin by asking you about GEB and Douglas Hofstadter, how you first met him, etc.

SN: I was around 12 when I first met Douglas. Our family was visiting Stanford, where he lived. His father was the Nobel Prize winner, Robert Hofstadter. And I remember that Doug and my brother were all excited about mathematics and logic. And I was the younger kid looking up and not really understanding any of the words that they’re using, but sensing their excitement that this must be very deep stuff. But I hung around and listened because that’s what younger brothers do, I think.

And I remember we worked on some problem that they invented, and it escapes me now exactly what that problem was. But it was something to do with a recursive function, where we get the next term by looking at the previous terms. And it had some interesting properties which they were playing with.

And they were excited about this but I was just a young kid brother in the way. So, that was the first time we met, around 1960. Doug says something about that in his foreword to Gödel’s Proof.

And then we ran into him every once in a while, I guess, but then I saw him more when he was a graduate student at the University of Oregon. He was working on the problem that became what’s known as Hofstadter’s butterfly.

That was his thesis topic, as I recall. And then I ran into him, and he described some of that to me. I didn’t know that he was putting it all together in a book. So then a variety of these things all came together in GEB.

It was a lot about self-reference: Bach with his fugues, Escher with these fun drawings and Gödel with the proof, but tied in with these other kinds of questions which somehow referred to themselves.

MM: And I think he had some sort of Scientific American contest about the Prisoner’s Dilemma. He sent out a letter to 20 people and you had to explain whether you choose to cooperate or defect. He writes about this in Metamagical Themas,

Sidney Nagel was very displeased with his conclusion. He expressed great regret: “I actually couldn’t sleep last night because I was thinking about it. I wanted to be a cooperator, but I couldn’t find any way of justifying it. The way I figured it, what I do isn’t going to affect what anybody else does. I might as well consider that everything else is already fixed, in which case the best I can do for myself is to play a D (defect)”.

SN: Yeah, it’s a good problem. Why did I choose to defect? Well, if the job is to just do the best for yourself, and no one knows, then that’s the solution. The question is whether you believe everyone else could actually cooperate, but cooperation needs you to talk to people. You can’t cooperate alone. So it’s a dilemma. It shows you the world is a complicated one.

MM: On the first day of our class, you had mentioned that you were an English major, and you took this class on E&M. And, chapter 5 of Purcell’s E&M textbook compelled you to switch to physics. Can you recollect some of those memories and experiences, and how that happened?

SN: I started off as an English major, or that’s what I thought I was going to be, I was excited about literature. But then I wasn’t interested in what they said about the literature, and then I somehow also realized, oh, you have to be able to write well. So there were those things, and then I was looking for something else to be interested in.

And I took the honors physics class, which uses the same textbook of Purcell which we are using, albeit an earlier edition. It was a lovely book, and I hope people still find it lovely. The part that made it special for me was at chapter 5: the analysis of how the electric field lines transform under relativistic effects and what this looks like.

I liked that, but I didn’t understand it very well. You know, I struggled with it and I didn’t know how to study physics very well at the time. And it wasn’t as if I did great in the course, but I thought hey, maybe I'll take another physics class. And so I didn’t switch over immediately, but then I had another class on E&M, and the teacher was wonderful, he really inspired me.

MM: You also said that Faraday is your hero, could you say more about that?

SN: Part of it is that of all the laws we’ve come up with in E&M, Faraday’s Law is perhaps the prettiest. It just makes you go ‘Wow, nature does that. Wow, look at that. Isn’t that neat?’

And then you stick around physics, and we started looking at physics and dynamics of sandpiles. And lo and behold, Faraday had looked at that too in his own way. So he was just a very curious physicist whose mind was open to all the phenomena at the time, and it didn’t matter whether it was one subject or another. We hadn’t pigeonholed things at that time into this sub-field or that sub-field. Faraday looked at all these different things.

And then I also appreciated the fact that he was kind of a self-taught person. I don’t think he had a great mathematical education, but his way of dissecting a problem was in an experimental realm, which is beautiful.

But by looking and looking and looking very carefully he was able to come up with these deep concepts such as a field. And the reason we know about fields is Faraday.

MM: You also said once in class that the optical properties of an object, how it appears, relates to its thermal and electrical properties. Could you say more about that?

SN: [Holds two forks, one metal and one plastic]. What are these? They’re two forks. But I’m looking at them, and this one reflects back at me, and the other one I can see through.

Just by looking at it, I know something about it. If I stick [the metal fork] into an electric outlet, I will kill myself. If you have something that looks like this [plastic fork], if I stick it into an electric outlet, I will not kill myself.

So just by how this thing looks, I can tell the difference. So this tells me that the electrical properties are somehow related to the optical properties. And then you also know that if I stuck this into boiling lead, [with the plastic fork] I won’t burn myself, whereas with this [metal] one, I will.

Oh, so that means that the optical properties also affect the thermal process. So these things are all related. And when I was writing up my PhD thesis, I remember thinking about that, so I wrote that down in the introduction to my thesis.

MM: Your office is a beautiful collection of many different things, I’m curious if you have any hobbies outside of physics.

SN: Yes! I enjoy woodworking. I just think carpentry is beautiful, and it’s nice and it smells good, it feels good. So I was trying to build things. And when research isn’t going well and you have a hobby like that, then you think about that instead of your research, and it gives you an outlet for still trying to be creative.

Then as part of my fluid mechanics research I got very interested in photography. So I spent a lot of time trying to really make the images as special as I could because it’s not just the intellectual question of the science. We are not just scientists but also humans. And we humans respond to the science, of course, but also to the aesthetic qualities.

Then, unfortunately, the world went digital, and digital photography doesn’t appeal to me as. With the analog stuff you would go into your dark room and you get all these chemical smells on your fingers and I love that.

And then, during the pandemic, we were all stuck at home, and so I tried to write poems about physics. And again, like all my hobbies, that went on for a while and then stopped. And now I’m hoping that something else will get me excited.

In terms of writing, the one writer who I would like to emulate, if it were possible, is a biologist who was around in the 60s and 70s. His name is Lewis Thomas, and he wrote books and essays about biology. Many books are trying to teach you something. But what I liked about Lewis Thomas is that he simply helps you appreciate something.

MM: In your interactions with all these leading physicists, are there any anecdotes that stand out?

SN: Well, the anecdote that stands out to me is about Purcell, whose textbook we are using. I got to meet Purcell. He came to Chicago to give a talk once. I arranged a dinner with him and my research group.

By the way, I had a cat who I had named after Purcell. Purr-cell is a good name for a cat. I didn’t tell him that I named the cat after him, because I wasn’t sure whether he would be happy or offended. But the story he told us over dinner was very good.

So Purcell’s main research was on nuclear magnetic resonance (NMR). And then there’s another physicist who was actually my teacher, for the second E&M class I took, who is also a Nobel Prize winner, Polykarp Kusch. And Kusch was also an experimentalist, and he got the Nobel for precision measurements of the magnetic moment of the electron and muon. These were very high-precision experiments.

And one time Kusch went to see Purcell’s lab in Harvard. And there was a vacuum can in the middle with a bunch of wires. So Kusch was looking at this, and there were red globs on it. Back in those days vacuum technology wasn’t what it is today and there was a tiny leak in the can. We would use something called Glyptal, which was a kind of red paint that would somehow help clog up the leaks.

And Kusch was looking at this, and this was magnetic resonance, remember. And Kusch asks, I wonder why that stuff is red. And he asked, what would be red? Well, iron oxide would be red. Iron has strong magnetic properties.

So here he was doing these experiments on NMR, he’s painting iron stuff on top of it and he hadn’t thought about it. Purcell said “it never would have occurred to me to ask that question”, but Kusch asked the question because he’s interested in all these ways that experiments can go wrong. If you’re gonna do a precision experiment, you have to get all these little things right.

And this story shows that there are many different kinds of physicists. One can be really good at something, and another can be really good at something else, and they don’t have to be the same things. And there’s a role for each of them in physics.

And so Kusch was a great physicist doing precision measurements, Purcell was also great in doing a very different kind of physics. And neither of them could have done what the other one did.

Feedback and reading recommendations are invited at malhar.manek@gmail.com

Once in a while, you get to meet a Nobel Laureate. Kip Thorne did a Zoom session in November. John Jumper gave an in-person talk last week. Here are some memorable insights from listening to those who have expanded the frontiers of knowledge.

Kip Thorne said he was never the stereotypical ‘bright’ physics student who intuitively understood everything the moment it was presented. Instead, he would learn by starting from scratch on pen and paper, and re-derive every result for himself.

In his Zoom background, there were several large cardboard boxes. Turns out, the boxes stored all the notebooks Kip had filled with equations over the years.

John Jumper is jovial. He cracked a couple of jokes that left everyone in splits.

He said that at Google DeepMind, it felt like he was attending a machine learning conference every single day. The best minds doing ML research were down the hall from his office.

While he was doing his PhD at UChicago under Prof. Tobin Sosnick (who was sitting in the front row), he was a teaching assistant for an undergraduate general chemistry class. Apparently, he wasn’t very good with chemistry at the time (he did his undergrad in physics), and he managed to stay one week ahead of the content of the class he was TA-ing.

John Jumper’s talk was technical; Kip Thorne’s wasn’t. Regardless, it wasn’t so much the content of what they were saying that stuck with me. Rather, it was the vibe and aura of hearing them speak that was greatly inspiring.

It is easy to get lost in the day-to-day grind of classes and problem sets. But once in a while, it is important to be inspired, see the big picture. Unlike Edison, I think it’s 99% inspiration, 1% perspiration.

Yale has secret societies, like Skull and Bones, Scroll and Keys etc., that are only for seniors (fourth-year students). Every existing member can ‘tag’ or nominate a certain number of people from the next class, and people are invited for interviews based on these nominations (you cannot apply to the secret societies). One of the very selective secret societies also asks for 3 professor recommendations. The Bush family (former US president) used to host Skull and Bones for an annual lunch event, since George H. W. Bush was part of that society when he was at Yale. But apparently, somebody once criticised Bush and, no prizes for guessing, they discontinued the lunches after that.

Touring MIT, even as an outsider, was an inspiring experience. I got to see the numerous labs in action, exemplifying MIT’s philosophy of applied knowledge — ‘minds and hands’.

The MIT Museum had many artifacts and exhibits about Claude Shannon — my role model. His juggling machine WC Fields, thinking mouse-maze machine Theseus, chess-playing machine Endgame, and other gadgets like Nimwit and Red/Black were all on display. I had a blast!

There is a train station called Harvard Square and another one called Kendall/MIT. Simply walking around that area, one finds so many inspiring plaques and inscriptions.

One of the squares near the MIT campus area is literally called Technology Square. Google and Meta have their research buildings there. Broad Institute (joint Harvard-MIT biological research institute which holds the CRISPR patents), McGovern Institute for Brain Research and others are located there too.

Now, some fun stories from my conversations in Boston!

David Shaw is a hyper-optimiser. Whenever he wants to fly somewhere, he first sends 2-3 assistants to that destination via different routes — they report back on which was the quickest, and then he takes that route. He hedged his donations, giving to multiple elite universities, so that his kids would have an advantage in the admissions process no matter where they wanted to attend college. He wears a black t-shirt and khaki crew shorts everywhere he goes.

Edward Boyden works at the McGovern Institute for Brain Research at MIT. He is a whiz kid genius of sorts: started college at 14 at MIT, graduated at 18 with 3 degrees (physics, electrical engineering and CS), finished his PhD from Stanford at 21. He works in a glass office, so his awards — which he has tons of — cannot hang on the wall; instead, they lie on the floor as if they are worthless. A friend once went to Ed Boyden’s office for a PhD interview, and Boyden asked him to have a seat. But the Breakthrough Prize for Life Sciences was lying on the floor next to the chair, so my friend couldn’t even move the chair!

In graduate school, the currency you are measured by is the quality of your ideas. PhD students optimise a lot for generating good ideas — this often means relentlessly monitoring diet, sleep and exercise; pursuing deep work; eliminating alcohol completely; and using Obsidian extensively for taking notes.

Gödel, Escher, Bach was the first time I experienced magic. Zero To One was the second.

I have since become a fan of Peter Thiel’s ideas on technology, business and investing, voraciously listening to his podcasts, pouring over Blake Masters’ original class notes, and scouring the internet for anything he has written (like this treasure trove). Not to mention reading Cryptonomicon (which was required reading at PayPal), The Founders (a book about PayPal — I even spoke with the author), and René Girard’s writings (as we’ll see soon).

Here is my understanding of Peter Thiel’s philosophy — or, as I like to call it, Thieleology. An overview of this essay:

1. Anti-Anti-Anti-Anti Contrarian

2. An Education in Philosophy

3. Competition is for Losers

4. Hunting for Secrets

5. The Applied Philosopher

6. Definite Optimism

7. The Motivation Question

8. With Peter Thiel’s Complements

9. Some Contrarian Truths

10. Bonus!

If there is one thing I hope to convey through this essay, it is a better appreciation for the rich connections between Thiel’s various ideas.

Disclaimer: I have never met Peter Thiel (though I would love to). All wisdom is Peter’s; any mistakes are mine.

First, who is Peter Thiel, and why should you care? Peter co-founded Confinity in the 1990s, which later merged with Elon Musk’s X.com to form the PayPal we know today. He was the first outside investor in Facebook, and his VC firm Founders Fund has made legendary investments in SpaceX, Stripe, Palantir and others. Among other things, he has been a big backer of JD Vance’s political career and has set up the Thiel Fellowship, which gives college dropouts $100K to build something.

This is Peter Thiel as the world knows him. But who is he, really? That’s what this essay is about.

Anti-Anti-Anti-Anti Contrarian

(Inside joke: this weird subheading is inspired by Thiel’s talk titled “anti-anti-anti-anti classical liberalism”)

Today, Peter Thiel is famous for his contrarian question: ‘What important truth do very few people agree with you on?’ He is well-known for backing unconventional founders, from Mark Zuckerberg to Elon Musk. But once upon a time, Thiel was as close to the dictionary definition of ‘conventional’ as one could possibly be.

In his 8th grade yearbook, a friend predicted that Thiel would go to Stanford for college. Not only did this prediction come true, Thiel continued on at Stanford Law School, and almost became a Supreme Court clerk. The man famous for being contrarian was once knee-deep in the rat race of prestige.

What changed this? I reckon there were 2 big influences.

First, Thiel studied under René Girard at Stanford — a name that will keep recurring throughout this essay.

René Girard says there are two kinds of desire: physical and metaphysical desire. Physical desire is wanting an object for its inherent qualities, like a glass of water because you’re thirsty — or learning for the sake of learning. This is healthy.

Metaphysical desire is different. Acquiring the object only brings you joy because of the person it makes you become. You only care about it because of what it says about you — like learning for good grades or a diploma. This is unhealthy.

— David Perell

The second — the late-90s business battle of PayPal v/s X.com — is more nuanced, and leads us to our next topic of discussion.

An Education in Philosophy

Ever since I learnt that Thiel studied philosophy in college, I’ve wanted to get a sense for what an academic study of philosophy actually looks like. So, my first quarter at the University of Chicago, I took a class called Philosophical Perspectives.

From what I’ve understood, academic philosophy forces you to think deeply about complicated questions. For example, when we read Oedipus Tyrannus for our class, we were asked to think about questions like, is it the story of a rise or a fall? Is Oedipus better off at the start or the end of the play? If a king is someone who is born into monarchy and a tyrant is someone who earns the crown through their efforts, was Oedipus the king or the tyrant of Thebes?

More generally, philosophy asks questions like, to what extent does meaning reside in the interpreter v/s the message? Is there free will? Do we compete because of our similarities or our differences? Is interiority a complement or a substitute to exteriority?

There are no straightforward answers to such questions. My professor kept telling us that the key to success in academic philosophy is the ability to take a risky, unconventional stance, and then back it up with reasoning and textual evidence.

A great philosophy paper, my professor explained, involves sticking your neck out by arguing for a bold, contrarian thesis — for example, saying that Oedipus is better off at the end, when he is blind, exiled and disgraced, than at the start, when he is the beloved ruler of Thebes — and then corroborating the thesis by logical reasoning and evidence.

Seen through this lens, one can see hints of a philosophical mind in all of Thiel’s talks and writings: contrarian beliefs grounded in facts.

Competition Is For Losers

One of the questions that philosophy is concerned with is, do we compete because of our similarities or our differences? René Girard thinks, as does Thiel, that we compete with those who are similar to us.

Paradoxically, I think the polarization masks the increasing sameness of the two major parties. They hate each other more and more, as they become more and more alike, like the Capulets and the Montagues in “Romeo and Juliet”...

— Peter Thiel, Reddit AMA

As René Girard’s mimetic theory of desire suggests, metaphysical desire arises when we compete for the same things.

Overachieving high school students with the same application profiles — strong GPA and near-perfect SAT scores, student council, model UN, ‘research’, internships — fight tooth and nail over admissions into the same few elite universities. In this case, the physical desire of learning and seeking knowledge for its own sake gives way to the metaphysical desire of the ‘Ivy League’ brand value.

Browsing the merch store of an elite university is an insightful experience: you realise how people are willing to pay $100 for a Harvard hoodie; take away that logo and they probably wouldn’t pay $20 for it. Elite-college-bookstores are the unseen version of Louis Vuitton.

Once they reach college, most of these high-flying high-schoolers get funneled into the same few paths — pre-med, computer science, economics/finance — and compete fiercely over the most prestigious on-campus clubs and internships. Many go on to chase the same few jobs — consulting, finance, AI — even the STEM majors get enticed into quant hedge funds — and the new brand on the resume becomes Goldman Sachs.

Guess what? The passion project that you have so much fun doing (this blog, in my case) doesn’t bolster your resume; a prestigious brand name does. By competing with others, you are competing away the stuff that makes you interesting. Competition is for losers. (There is a caveat to this: competing with others is awful; competing with yourself, though, can be magical. More on this soon).

If you’re in the US and go to a good school, there are a lot of forces that will push you towards following train tracks laid by others rather than charting a course yourself. Make sure that the things you’re pursuing are weird things that you want to pursue, not whatever the standard path is. Heuristic: do your friends at school think your path is a bit strange? If not, maybe it’s too normal.

— Patrick Collison

Ardent Thiel-interview-watchers know that he often brings up the question of what education is in economic terms. What does the value of education derive from? Is it an investment? A consumption good (“four year party”)? An insurance policy?

Thiel’s answer — which makes perfect sense when you understand his ideas on competition and Girardian mimetic desire — is that education is a tournament. The value of education in today’s world, Thiel thinks, derives primarily from the fact that the elite universities exclude people. Just like the long queues of people waiting to just enter a Louis Vuitton store, the more exclusive you make it, the more valuable it gets.

To untie the knot of desire, we have only to concede that everything begins in rivalry for the object. The object acquires the status of a disputed object and thus the envy that it arouses in all quarters, becomes more and more heated…

The value of an object grows in proportion to the resistance met with in acquiring it. (Read: the value of the Ivy League is inversely proportional to its acceptance rates). And the value of the model grows as the object’s value grows. Even if the model has no particular prestige at the outset, even if all that ‘prestige’ implies — praestigia, spells and phantasmagoria — is quite unknown to the subject, the very rivalry will be quite enough to bring prestige into being.

— René Girard, in Things Hidden Since the Foundation of the World

Ordinarily, businesses increase supply in response to a surge in demand — except, like LVMH, the elite colleges don’t do this. If the role of the university is primarily to impart knowledge, it would make sense for them, Thiel thinks, to expand class sizes, so that they can educate more people. On the other hand, if the primary role of the university is to act as an exclusive club, then their current behaviour makes complete sense. The plummeting acceptance rates and skyrocketing tuition fees for top colleges over the last few decades seems to corroborate Thiel’s thesis.

Back to the story of a young Thiel climbing the rat race of prestige. Thiel explains in this interview that his mistake was to assume that education is a substitute for thinking about one’s future.

What are you going to do in life? I don’t know, I’ll get an undergraduate degree. What will you do after that? I don’t know, I’ll get a postgraduate degree. What will you do after that? I don’t know, I’ll work at a hedge fund/law firm/consulting firm and so on…

Hunting For Secrets

René Girard’s most famous book was literally titled Things Hidden Since the Foundation of the World: a profound clue for the Thieleology aficionado.

Unsurprisingly, perhaps, Thiel emphasises the importance of secrets — Things Hidden — as truths that lie somewhere between popular knowledge and unanswerable mysteries. Think of secrets as a 3-layer cake.

The first layer is fundamental v/s emergent. Physics and mathematics are fundamental. Economics, politics and psychology are emergent.

The second layer is contrarian v/s consensus. Contrarian ideas are those that very few people believe. Consensus ideas are mainstream, popular views.

The third layer is truth v/s falsehood.

Secrets, then, are simply contrarian truths. Fundamental contrarian truths are secrets of nature. Emergent contrarian truths are secrets of people. In the Bhagavad Gita, choosing Krishna over his entire army was Arjuna’s contrarian truth.

Unravelling secrets of nature is what mathematicians, physicists and astronomers do. Einstein’s theory of relativity was a secret of nature, since it was a contrarian idea (against the well-established, mainstream Newtonian theory) and it revealed a new truth about the universe.

Secrets of people are, in some sense, like the memo from Jerry Maguire: things we think but do not say. If discovering secrets of nature won Einstein the Nobel Prize, finding secrets of people skyrocketed Seinfeld to worldwide fame.

“[Claude Shannon is] a decidedly unconventional type of youngster” — Vannevar Bush (Shannon’s PhD advisor)

[Claude Shannon] had this counter-culture streak about him, and he was a non-conformist in the best sense. (From Jimmy Soni’s Reddit AMA)

Rory Sutherland’s book Alchemy — everything he writes and says, for that matter — is a masterclass on the craft of discovering people secrets. A few of my favourites from him: cyclists tend to be rude since they pay the price for losing momentum; the hidden role of dishwashers is to hide dirty dishes; specificity can act as a placebo. (My interview with him below).

Peter Thiel even helps us out by providing a general framework to think about contrarian truths: “most people think X, but the truth is the opposite of X”.

At this point, we can make sense of Thiel’s disdain for buzzwords, for they are the most obvious instance of the mainstream and the consensus.

“Big data” really means “dumb data.” — Peter Thiel, Reddit AMA

The Applied Philosopher

Most people think Zero To One is a business book, but the truth is that it is a deeply philosophical tome on how to build the future. Most people think Peter Thiel is a startup investor/tech VC, but the truth is that he is a profound thinker who applies his philosophy to startups and investing.

In Thiel’s view, the future is not simply a time that hasn’t yet occurred. It is a time that will be different from the present. If the world does not change significantly in the next 50 years, the future is still far away.

Moreover, Thiel thinks, the future will not be built by a single individual working alone, nor by large, bureaucratic, corporate organisations — the perfect middle ground, he thinks, is a startup.

Positively defined, a startup is the largest group of people you can convince of a plan to build a different future. A new company’s most important strength is new thinking: even more important than nimbleness, small size affords space to think.

— Peter Thiel, in Zero To One

Here is an example of Thiel’s philosophy of secrets, applied to startups.

Biggest mistake ever was not to do the Series B round at Facebook.

General lesson: Whenever a tech startup has a strong up round led by a top tier investor (Accel counts), it is generally still undervalued. The steeper the up round, the greater the undervaluation.

— Peter Thiel, Reddit AMA

Another example, on the business version of ‘competition is for losers’:

Most people believe that capitalism and competition are synonyms, and I think they are opposites. A capitalist accumulates capital, and in a world of perfect competition all the capital gets competed away: The restaurant industry in SF is very competitive and very non-capitalistic (e.g., very hard way to make money), whereas Google is very capitalistic and has had no serious competition since 2002.

— Peter Thiel, Reddit AMA

The best companies, as per Thiel, are born out of a secret (i.e., a contrarian truth), and use the cash flows that accrue from their secret to invest in deepening their monopoly.

Another secret in the business context is that the overwhelming majority of a tech startup’s present value accrues from future cash flows in years 10 and beyond.

Most of a tech company’s value will come at least 10 to 15 years in the future…

In March 2001, PayPal had yet to make a profit but our revenues were growing 100% year-over-year. When I projected our future cash flows, I found that 75% of the company’s present value would come from profits generated in 2011 and beyond—hard to believe for a company that had been in business for only 27 months. But even that turned out to be an underestimation…

If you focus on near-term growth above all else, you miss the most important question you should be asking: will this business still be around a decade from now? Numbers alone won’t tell you the answer; instead you must think critically about the qualitative characteristics of your business.

— Peter Thiel, in Zero To One

Definite Optimism

Now that we know what matters — secrets — the question is, how do we find them? To this, Thiel proposes a 2x2 matrix.

Remember, the future is a time that will be different from the present. Whether you think it will be better or worse than the present relates to optimism and pessimism.

Definite and indefinite pertains to whether your view of the future is grounded in a concrete plan or left to randomness. Thiel likens this to the difference between calculus (definite) and statistics (indefinite): calculus can concretely predict the behaviour of a system, while statistics can only ever make a vague, probabilistic estimate of the possibilities.

There are many ways one can think about this matrix. The version with a country/society in different stages is above. In fact, this relates to Ray Dalio’s model of changing world orders: a country is in the strongest phase of the world orders cycle when it is definite and optimistic (education and leadership being the leading indicators), and in the weakest phase when it is indefinite and pessimistic (loss of reserve currency status).

One could hypothesise that world order cycles proceed from definite pessimism —> definite optimism —> indefinite optimism —> indefinite pessimism.

Another version, with different occupations, is below.

Yet another version, with investment and savings, is below.

I love Iyengar yoga because it deeply ingrains in me the concept of definite optimism. Supreme health and control over the body and breath are possible (optimism), with effort and perseverance (definite).

Reddit user: Hi Peter … if you were not from United States, do you believe you could reach the same position as you are now?

Peter Thiel: One can never run this experiment twice, but...

I was born in Germany and my parents emigrated to the US when I was 1 year old. I think Germany and California are in some ways extreme opposites — Germany is pessimistic and complacent, California is optimistic and desperate. I suspect my life would have turned out very differently had we stayed in Germany.

***

Reddit user: What do you think is the most exciting example of a company showing “determinate optimism” today?

Peter Thiel: The dual Elon Musk empire of Tesla and SpaceX. (For context, this is from 2014)

— Reddit AMA

A definite world rewards conviction; the below excerpt from More Money Than God is fascinating.

One time the macro men feared that the markets would turn against their European bond position in the short term, and they advised [Julian] Robertson to protect Tiger from losses by putting on a temporary hedge.

“Hedge?” Robertson retorted angrily. “Hey-edge? Why, that just means that if I’m right I’m going to make less money.”

“Well, that’s right,” the macro men answered him.

“Why would I want to do that? Why? Why? That’s just dirt under my fingernails.”

— Sebastian Mallaby, in More Money Than God

The Motivation Question

At one point during their podcast, Joe Rogan asks Peter Thiel about the Egyptian pyramids. The clip is almost funny to watch: Rogan keeps asking ‘how’ they built the pyramids, while Thiel keeps evading the question and focuses on ‘why’ they were motivated to build them. As David Perell writes, “[Thiel] doesn’t just focus on the brushstrokes. He looks at how the painting is framed.”

If you believe that ‘where there is a will there is a way’ (as a definite optimist would), then it is obvious that the important question to focus on — the constraint, the bottleneck — is not ‘what is the way?’ but ‘what is your will/motivation?’

Similarly, consider Thiel’s insights on AI from 2014:

I think AI is still a fair ways off. But the economic questions (e.g., how will this impact our work?) are secondary to the political questions (e.g., will AI be friendly?).

The development of AI would be as momentous as the landing of extraterrestrials on this planet. If aliens landed, the first question would not be about the economy!

— Reddit AMA

With Peter Thiel’s Complements

Perhaps you noticed the typo — but that was intentional! For one of the overarching contrarian truths in Peter Thiel’s philosophy is

Reddit user: When you backed Elon Musk with SpaceX, was it because you believed in/knew Elon, thought space travel was important, or because you were looking for a return?

Peter Thiel: All three.

In his podcast with Joe Rogan, Thiel asks the question of interiority (focus on inner self as in Eastern philosophy, e.g., yoga, meditation) v/s exteriority (focus on outer world as in Western philosophy, e.g., material possessions, space travel) — are they complements or substitutes? Is improving the inner self a first step that enables external progress? Or is it a substitute where attention is reallocated from external exploration to inner consciousness?

My personal answer is that they are complements, which also fits well with the ancient Greek idea of man as a mini-world:

What made Vitruvius’s work appealing to Leonardo and Francesco was that it gave concrete expression to an analogy that went back to Plato and the ancients, one that had become a defining metaphor of Renaissance humanism: the relationship between the microcosm of man and the macrocosm of the earth.

This analogy was a foundation for the treatise that Francesco was composing. “All the arts and all the world’s rules are derived from a well-composed and proportioned human body,” he wrote in the foreword to his fifth chapter. “Man, called a little world, contains in himself all the general perfections of the whole world.” Leonardo likewise embraced the analogy in both his art and his science. He famously wrote around this time, “The ancients called man a lesser world, and certainly the use of this name is well bestowed, because his body is an analog for the world.”

— Walter Isaacson, in Leonardo da Vinci

On the question of interiority, I also resonate strongly with a quote from the Stoic philosopher Epictetus: “What else is tragedy but the portrayal in tragic verse of the sufferings of men who have devoted their admiration to external things?”

This brings us to a topic we touched on earlier. Competing with oneself — say, by periodically reflecting, introspecting and course-correcting — as opposed to competing with others, is an element of interiority. In fact, the Hindi language has distinct words for these, derived from Sanskrit: प्रतिस्पर्धा implies competing with others, while अनुस्पर्धा implies competing with yourself (those familiar with Hindi should watch this video). Google Translate, interestingly, obscures the difference:

As you think about this, I would encourage you to connect the dots with other aspects of Thieleology. Here is my synthesis:

1. The motivation (why) question relates to optimism v/s pessimism, which relates to interiority (what drives you to do something? Curiosity, ambition, revenge? Do these motivations pertain to a brighter future or a gloomier one? How does understanding your motivations improve your understanding of yourself?)

2. The engineering (how) question relates to definite v/s indefinite, which relates to exteriority (do you have a concrete/definite plan to implement your vision or a vague/indefinite perspective? How do you need to engage with the external world to execute your plans?)

3. Therefore, interiority and exteriority are complements, which, when optimally aligned, lead to definite optimism (building the future you envision).

Some Contrarian Truths

Inspired by Zero To One, I have a section in my personal notes Google Doc where I note down contrarian truths that I think of. My list has 23 contrarian truths as of now; here are my favourites.

1. Most people think that building good habits requires ‘willpower’ and ‘self-control’ in avoiding temptations, but the reality is that building systems and minimising friction matters more.

2. Most people focus on the demand side, but supply is more important (Marathon Asset Management, Capital Returns).

3. Most people focus on probabilities, but payoffs are more important (Nassim Taleb, The Black Swan).

4. Most people think The Shawshank Redemption is a prison escape movie, but in fact it has deep philosophical meaning, e.g., power of writing, perseverance (tunnelling through the wall), power of knowledge/education etc.

5. Most people focus too much on what to do (e.g., what book to read), but when to do something matters more (e.g., when to read it) — what is the right time — As Morpheus says in The Matrix, “more important than what is when”.

6. Most people think entrepreneurs take risk, but the reality is that they minimise it.

7. Every deep thinker must necessarily think deeply about the meta question, ‘what questions are worth thinking deeply about?’ Every deep thinker must not only play a game well, but also, importantly, ask what games are worth playing.

8. Most people think in terms of substitutes (A or B), but the truth is that complements are more valuable (A and B): man and machine, fundamentals and technicals in investing, top down and bottom up, interiority and exteriority.

9. Most people often (implicitly) choose to succeed at trivial things, but it is better to fail at nontrivial things. Poverty of ambition is underrated.

10. Thiel says there are two views of philanthropy: the American view is that the philanthropist is a selfless person with a desire to give back to society; the European view is that the philanthropist is atoning for their wrongdoings by giving up wealth. Thiel agrees more with the European view.

    Similarly, if you are getting 100% on an exam, the consensus interpretation is that you are doing very well. The contrarian view, that is worth considering, is that maybe you are not taking a sufficiently challenging class.

    Likewise, if you are not falling while learning ice skating or skiing, that means you are not trying enough.

    Elon Musk is a big advocate of deleting things from a manufacturing process — he says that if you don’t end up adding things back later, it means you aren’t deleting enough.

    

Bonus

Reddit user: Do you follow sports? What's your favourite sport? Favourite team?

Peter Thiel: In the Soviet Union, chess was considered a sport — and I think that’s the one thing the communists got right.

So, you’re intrigued after reading this essay and want to learn more about Thiel?

Here’s my favourite Thiel video, one that I would very strongly recommend watching:

I thoroughly enjoyed reading David Perell’s essay about Peter Thiel, and would highly recommend it. Some excerpts below:

Some of Thiel’s favourite books:

Feedback and reading recommendations are invited at malhar.manek@gmail.com

There was a young fellow from Trinity

Who took the square root of infinity

But the number of digits

Gave him the fidgets;

He dropped Math and took up Divinity.

George Gamow, in One, Two, Three...Infinity

Infinity is a strange beast. Thinking about it boggles the mind. What does it even mean? Is it a number? Is it a concept? What happens if I add infinity to itself? Does it get bigger?

I, for one, have spent many an hour puzzling over such questions. Turns out, I wasn’t the only one asking them. In a 1925 lecture, David Hilbert presented that rare delight — a thought experiment in pure mathematics — the Infinity Hotel.

Here’s how it works. There are an infinite number of rooms, one for each positive integer: 1, 2, 3 and so on.

Suppose a new guest arrives. Then, the management of the Infinity Hotel simply requests every guest to shift to the room with the next number, and the new guest is accommodated in room # 1. Adding a finite number to infinity doesn’t change its size.

Suppose, instead, that a bus full of infinitely many guests arrives. Then, the management of the Infinity Hotel simply requests every guest to shift to the room with twice their current room number, and the new guests are accommodated in the odd-numbered rooms. Multiplying infinity by a finite number doesn’t change its size.

But things get even more interesting. Suppose there are infinitely many such buses, each with infinitely many guests — they can all still be accommodated at Infinity Hotel! Even multiplying infinity by itself doesn’t change its size!

So is there simply one supreme, all-encompassing infinity?

I wish matters were that simply. (Un)fortunately, they’re not. There are many different sizes of infinity.

How come? If even multiplying ∞ by itself doesn’t change its size, then what does? The answer to this question is fascinating — firstly, because it is derived from deep concepts in set theory; and secondly, because it leads us to the mesmerising territory of the Continuum Hypothesis.

At the level of first principles, what does it mean to count? Formally defined, we count by creating mappings.

Suppose I have 5 books. Then, I construct a mapping from the first book to the number 1, from the second book to the number 2, and so on. When we can create such a one-to-one correspondence between two sets, we say that they have the same size.

Ergo, it is possible to create a one-to-one correspondence between:

• the positive integers and all the integers (including 0 and negative integers)

• the positive integers and the even (or odd) integers

• the positive integers and the prime numbers

• the integers and the rational numbers (fractions)

Thus, we know that they all have the same size. We also know that each of them is an infinite set, so we denote this infinity — the smallest size of infinity — by א‎_0.

Turns out, the size of the real numbers — every number that has a positive square, including π, e, and √2 — is much greater than א‎_0. In fact, if we call the infinity of the real numbers א‎₁, we know that א‎₁ = 2^(א‎₀)_.

What’s more, we know that 2^(א‎₁) must be greater than א‎₁, and two raised to that must be even greater, and so on. Thus, there are infinitely many sizes of infinity!

Now, the Continuum Hypothesis asks, is there an infinity whose size is between א‎₁ and 2^(א‎₀)? Do infinities have discrete sizes? I wish we could ponder these questions, but I’ll stop here, lest this post becomes infinitely long...

Feedback and reading recommendations are invited at malhar.manek@gmail.com

But one of the more interesting spots on campus — one that feels like it’s pulled right out of Hogwarts — is the Arley D. Cathey Learning Center. Quite an interesting name linguistically, isn’t it? Not library, not reading room, but learning center.

That got me thinking: how do we learn? How does the experience of learning relate to the physical processes of neurons in the brain? Are all methods for studying and note-taking equally effective, or some more so than others? Let’s find out!

Active v/s Passive

Right now, I’m taking a class called Honors Calculus (Inquiry-Based Learning). Here’s how it works. There are no lectures and no textbooks. Students prove theorems on their own and volunteer to present these in class. The professor then guides the interaction that follows, often discussing different ways of proving the same theorem. Fun!

At the most basic level, there are 2 ways of learning: active and passive. Active learning, like my math class, involves deliberate practice by solving problems. Passive learning, like most high school and college lectures, involves listening to someone else solving problems. In some sense, active learning is bottom-up, while passive learning is top-down.

What research shows is that in terms of understanding — being able to reproduce ideas with explanations, at will and from scratch — active beats passive every single time. It’s not even close. The paradox is that active learning is effortful and uncomfortable at first, while passive learning feels easy.

A gym analogy is useful. To strengthen your muscles, you need to lift weights. This is difficult, but it will yield results. Watching others lift weights is of no value.

But what I find even more interesting about experimental findings is that active learners show epistemic humility. Have you ever played the card game where you predict the number of tricks you’ll make? This is similar. Not only do active learners know more than passive learners, they are also epistemically humble — they think they know less than they actually know.

Optimal Study Methods

The simplest way to implement this is in how we take notes. Most people take notes by simply transcribing what the book or speaker is saying. The much better way is to take notes by asking questions.

For example, instead of writing ‘Thiel says philanthropy is a form of penance’, one could write ‘What does Thiel think about the European v/s American views on philanthropy?’

This way, reading notes becomes an active process of thinking about big questions and re-deriving ideas, instead of passive review.

Here are some other ways to optimise learning:

1. Study alone, not in groups.

2. Eliminate distractions, set your phone to ‘do not disturb’, turn notifications off.

3. Don’t slog in one long session. Instead work for 45-60 minutes on, 15 minutes off.

4. Get deep rest, either in sleep or through yoga nidra. The re-wiring of neurons is catalysed by deep work. Neural connections physically change during deep rest.

5. Teach fellow students who are in the same class (or anyone else). Teaching out loud in complete sentences forces you to understand an idea deeply.

In some sense, all of the world’s knowledge is available at our fingertips, in the form of e-books, YouTube videos and more. For example, MIT freely shares lecture recordings, slides and homework problems for every single class — in theory, anyone can get an MIT education.

But learning is not a resource-availability problem: it is a motivation problem. Climbing the stairs to the top floor of the library is physical effort — yet, I speculate that doing so will (subconsciously) lead to more productive learning.

Feedback and reading recommendations are invited at malhar.manek@gmail.com

A similar (though somewhat weaker) question is, can a mutual fund run by Blackrock invest in Blackrock the asset management company?

Take a look at this picture — Drawing Hands by M. C. Escher.

Now consider the Epimenides paradox: ‘This sentence is false.’ Is the statement true or false?

Such self-referential paradoxes plagued mathematics in the early 1900s, most famously as Russell’s paradox. Then came along Kurt Gödel, who in 1931 published a dense paper that left all of mathematics stunned. It showed that there must be true statements in number theory (or any axiomatic system) that cannot be proven to be true. In other words, there are ‘gaps’: unreachable truths.

The finer nuances of Gödel’s proof are far too convoluted, but a big picture view of his method — as in Nagel and Newman’s 90-page book — is accessible to anyone who is so inclined.

From Russell to Richard

Suppose that, in a given city, there is a barber who shaves all those who don’t shave themselves. Now, does the barber shave himself?

This is an incarnation of Russell’s paradox: suppose normal sets are sets that do not contain themselves as members (e.g., the set of books is not a book itself) and abnormal sets are those that do (e.g., the set of all things is itself a member of the set). Now, is the set of all normal sets normal or abnormal?

Another way of posing such a paradox was formulated by Jules Richard. Suppose one creates a numbered list defining various types of numbers, such as:

1. Irrational numbers are those that cannot be written as a fraction of two integers

2. Odd numbers are those that when divided by two, leave remainder one

3. Prime numbers are those that are divisible only by one and the number itself

and so on. Notice how the number 1 is not irrational, the number 2 is not odd, and the number 3 is prime.

Now, by this categorisation, let us call 1 and 2 type-A numbers, and 3 a type-B number. Let us append this definition to our original list:

1. Irrational numbers are those that cannot be written as a fraction of two integers

2. Odd numbers are those that when divided by two, leave remainder one

3. Prime numbers are those that are divisible only by one and the number itself

4. Type-A numbers are those where the numeral corresponding to the definition, when viewed as a number, does not have the property described by the definition

Notice that linguistically, a distinction must be made between numbers and numerals. The Richard paradox asks, is the number 4 type-A or type-B?

Think back to the BSE question I posed at the beginning. Notice the distinction between the levels of corporation and platform. A similar distinction must be made between numeral and number.

In fact, abstracting away the minutiae, there is in each of these problems a hierarchy of levels of reasoning. The gist of every single one of these paradoxes is that there are statements ‘in’ the system and ‘about’ the system — and that paradoxes arise when meta-sentences are spoken on the same level as ‘mere’ sentences.

Gödel’s Magic

What Gödel realised is that every statement in number theory can be written in a formal language of mathematical symbols. For example, the statement ‘there is no natural number whose successor is 0’ can be written as:

Moreover, every symbol in this formal language can be assigned a unique number. For instance,

• ~ corresponds to 1

• ∃ corresponds to 2

• x corresponds to 3

• : corresponds to 4

• S corresponds to 5

• = corresponds to 6

• 0 corresponds to 7

and so on.

Since every theorem can be written as a string of symbols, and each symbol assigned a number, every theorem can be given a unique Gödel number.

To do this, raise every successive prime number to the exponent of the symbol and multiply them. For instance, the Gödel number of the theorem [~∃x: Sx = 0] is,

I know what you’re thinking. Isn’t this elaborate procedure merely an arbitrary way to name things, plucked out of thin air? It is — at least it seems so at first. But hold that thought.

The magic of Gödel’s system is that a theorem and a meta-theorem and a meta-meta-theorem all have a Gödel number: the hierarchy of levels is flattened! Statements ‘in’ the system and ‘about’ the system all have a Gödel number that can be cross-compared — without causing paradox.

One way to gain an intuition for this is, Gödel’s method creates a way to achieve paradoxical ends without paradoxical means.

As for the elephant in the room: the procedure of Gödel numbering that seems arbitrary at first is actually deliberately and carefully designed. It cleverly uses the fundamental theorem of arithmetic, which says that any number has a unique decomposition into prime factors.

This guarantees that every theorem has a unique Gödel number — and also ensures that, given a Gödel number, we can retrieve the theorem it represents.

As for the assignment of numbers to symbols, you could very well choose to let ~ correspond to 2, or any other number, instead of 1. The reason that doesn’t matter is, we’re usually not interested in calculating the actual Gödel number — they are astronomically huge, and of no real use. Take a look again at the Gödel number we wrote down: forget the entire multiplication, the last part alone (19^7) is equal to 893,871,739.

Funnily enough, the actual Gödel number is useless; what matters is the flattening of levels that it enables.

Feedback and reading recommendations are invited at malhar.manek@gmail.com

In any field, understanding first principles is valuable: what are the basic ideas that you know to be true?

In math, there are things like Euclid’s five axioms in geometry — but also more philosophical ideas of assuming as little as possible, demanding rigorous proof of theorems, and obtaining general theorems with broader scope rather than special cases (Taylor series over Maclaurin series, for example).

Likewise, as one remarkable polymath explained to me, “the main aim of yogasana is to keep the spine straight.” Another key, axiomatic insight in yoga is to focus on exhalation: if you exhale well, the inhalation will follow naturally.

Things become even more fascinating when you discover the idea of connectivities. My yoga instructor once commented, “paschim namaskarasana (reverse prayer pose) holds the key to mastering shirshasana (headstand).” I was intrigued: such connections come up all the time in math!

For instance, complex numbers are composed of a real and imaginary part, and can be plotted on an Argand diagram, which is simply a plane with the real part on the x-axis and the imaginary part on the y-axis. De Moivre’s theorem says that if you raise a complex number to the power of n, the modulus (distance of the point from the origin) is exponentiated and the argument (angle made with the x-axis) is multiplied by n. This can be understood in any number of ways — from Taylor series expansions to proof by induction — and leads to hyperbolic trigonometry and Euler’s identity.

Just as there are many ways of proving a mathematical theorem — Pythagoras’ famous theorem has more than 350 different proofs! — there are multiple ways of observing an asana. For instance, one can enter adho mukha svanasana by jumping back from uttanasana, or by raising the knees upwards from adho mukha virasana. As with mathematical proofs, each such path reveals and illuminates a different facet of the asana, or theorem.

One interesting element I’ve noticed in classical, Iyengar yoga is that the asanas themselves are static — for instance uttanasana as opposed to, say, alternate toe touch — but they are dynamic in the sense that the sharpness and focus in the pose are supposed to enhance with every exhalation.

I also find that with both math and yoga, pedagogical style is crucial. Especially, does a learner adopt a static, fixed mindset or a dynamic, growth mindset?

There will be asanas one cannot yet perform and theorems one cannot yet prove; the key is that one must not look at others who can seemingly do these “effortlessly” and think of oneself as being somehow “not smart enough” — instead one must ask, what am I missing? How can I get better? Or, as Christopher Begg says, persistent incremental progress eternally repeated (PIPER).

Here are two quotes from Guruji BKS Iyengar, the first from Light on Yoga and the latter from Light on Life.

“By performing asanas, the sadhaka first gains health, which is not mere existence. It is not a commodity which can be purchased with money. It is an asset to be gained by sheer hard work.”

“Physical health is not a commodity to be bargained for. Nor can it be swallowed in the form of drugs and pills. It has to be earned through sweat. It is something that we must build up.”

Cal Newport’s wonderful podcast with Andrew Huberman has a debate on deliberate practice v/s flow — deliberate practice is required to attain hard new skills (0 to 1), while a flow state is experienced when repeating what one is already proficient at (1 to n). In both, math proofs as well as yoga asanas, once one has mastered a certain technique or insight, it is easy to repeat — but the acquisition of that expertise to begin with requires sustained deliberate practice, or sadhana.

As you sit comfortably on a chair, each and every pose, when, with effort, perfected, it is as comfortable as one sitting on a chair.

— Guruji BKS Iyengar in a 1976 demonstration

Let me end with this extract from a biography of Leonardo da Vinci.

What made Vitruvius’s work appealing to Leonardo and Francesco was that it gave concrete expression to an analogy that went back to Plato and the ancients, one that had become a defining metaphor of Renaissance humanism: the relationship between the microcosm of man and the macrocosm of the earth.

This analogy was a foundation for the treatise that Francesco was composing. “All the arts and all the world’s rules are derived from a well-composed and proportioned human body,” he wrote in the foreword to his fifth chapter. “Man, called a little world, contains in himself all the general perfections of the whole world.” Leonardo likewise embraced the analogy in both his art and his science. He famously wrote around this time, “The ancients called man a lesser world, and certainly the use of this name is well bestowed, because his body is an analog for the world.”

— Walter Isaacson, in Leonardo da Vinci

Feedback and reading recommendations are invited at malhar.manek@gmail.com

Since then, I’ve come to develop this model for differentiated insights:

Δ consumption of content might relate to reading obscure rather than mainstream books, or consuming academic papers/podcasts/articles that others aren’t.

Δ interpretation is evident in the thought experiment that if Warren Buffett and I both read the same annual report, the Oracle of Omaha will glean far more insights.

In the spirit of Δ interpretation, I am sharing my understandings and interpretations from reading Peter Thiel’s Zero To One and Nassim Nicholas Taleb’s The Black Swan. While reading these books and thinking through their ideas, I had a number of insights from connecting the dots that I will elaborate in this post.

Quine’s Infinity of Interpretations

As it turns out, The Black Swan itself touches on this idea — logician W. V. Quine suggested that for any given set of facts, there could be an infinity of possible interpretations by different thinkers (somewhat like quantum mechanics, where interpretations range from Copenhagen to many worlds).

The Black Swan then points out the paradox that Quine’s hypothesis can itself be interpreted in infinitely many ways: “Note here that someone splitting hairs could find a self-cancelling aspect to Quine’s own writing. I wonder how he expects us to understand this very point in a noninfinity of ways.”

When I read this, I thought back to my favourite book, Gödel, Escher, Bach, which has a chapter (number VI) entirely on such ideas, and which argues for the universality of at least some messages. The Black Swan seems to agree:

Consider that two people can hold incompatible beliefs based on the exact same data. Does this mean that there are possible families of explanations and that each of these can be equally perfect and sound? Certainly not. One may have a million ways to explain things, but the true explanation is unique, whether or not it is within our reach.*

Thus, going back to my pseudo-equation above, in a message that has a single objective meaning, Δ interpretation = 0, hence Δ insights = 0. This may be a possible solution to the paradox inherent in Quine’s statement.

*If you are intrigued by this notion of explanations, I would recommend reading The Beginning of Infinity by David Deutsch.

The Future is Δ

Reductionism is an approach that seeks to explain everything in terms of fundamental rather than higher-level emergent explanations.

For example, consider one particular copper atom at the tip of the nose of the statue of Sir Winston Churchill that stands in Parliament Square in London. Let me try to explain why that copper atom is there. It is because Churchill served as prime minister in the House of Commons nearby; and because his ideas and leadership contributed to the Allied victory in the Second World War; and because it is customary to honour such people by putting up statues of them; and because bronze, a traditional material for such statues, contains copper, and so on.

Thus we explain a low-level physical observation — the presence of a copper atom at a particular location — through extremely high-level theories about emergent phenomena such as ideas, leadership, war and tradition. There is no reason why there should exist, even in principle, any lower-level explanation of the presence of that copper atom than the one I have just given.

Presumably a reductive ‘theory of everything’ would in principle make a low-level prediction of the probability that such a statue will exist, given the condition of (say) the solar system at some earlier date. It would also in principle describe how the statue probably got there.

But such descriptions and predictions (wildly infeasible, of course) would explain nothing. They would merely describe the trajectory that each copper atom followed from the copper mine, through the smelter and the sculptor’s studio, and so on. They could also state how those trajectories were influenced by forces exerted by surrounding atoms, such as those comprising the miners’ and sculptor’s bodies, and so predict the existence and shape of the statue.

In fact such a prediction would have to refer to atoms all over the planet, engaged in the complex motion we call the Second World War, among other things. But even if you had the superhuman capacity to follow such lengthy predictions of the copper atom’s being there, you would still not be able to say, ‘Ah yes, now I understand why it is there.’

— David Deutsch, in The Fabric of Reality

Likewise, a reductionist view of the future suggests that it is merely the set of temporal coordinates that have not yet occured. However, a more deep and interesting explanation is that the future is a time different from the present.

The future is interesting not because it hasn’t happened yet, but because it will be different from the present.

The Contrarian Question

Peter Thiel poses his famous contrarian question: What important truth do very few people agree with you on?

Good answers to the contrarian question are as close as we can come to looking into the future. (More on this soon.)

The Axes of Progress

There are two axes along which progress occurs: vertical (0 to 1) and horizontal (1 to n). These axes are orthogonal — i.e., perpendicular — which means that no component of one lies along the other (their dot product is zero). Simply put, vertical and horizontal progress are independent; “what got you here won’t get you there.”

This paradigm comes up in various domains:

• Economics, where developing economies (0 to 1) often adopt protectionism, which is disdained by developed economies (1 to n) who ‘kick away the ladder’ and prescribe one-size-fits-all policies. [I recommend reading Joe Studwell’s excellent book How Asia Works if you are interested in this.]

• Performance psychology, where deliberate practice is required to attain hard new skills (0 to 1), while a flow state is experienced when repeating what one is already proficient at (1 to n). [Cal Newport’s wonderful podcast with Andrew Huberman has a debate on deliberate practice v/s flow — my understanding is they correspond to 0 to 1 and 1 to n respectively, and are therefore orthogonal.]

• Those managing large family offices, endowments or pension funds are often incentivised to preserve capital (1 to n), as opposed to, say, an individual angel investor, who seeks to grow it at a rapid rate (0 to 1).

Terminal Value

When Peter Thiel ran some projections in 2001, he realised that 75% of PayPal’s value would come from cash flows generated after 2011, i.e., terminal value.

Similarly, when Elon Musk says that he expects Optimus to drive the majority of Tesla’s long term value, it is terminal value to which he is referring.

Terminal value is driven by growth and durability — the compounding formula is driven by rate of return (growth) and longevity of time period (durability).

While most analysts focus on short-term growth, the more important question to ask is, ‘will this firm be around 10 years from now?’ The best answers to this question arise not by crunching numbers on a spreadsheet but through an understanding of intangibles — especially enduring intangibles like people and culture. [One of the best ways to appreciate this point is to read The Founders by Jimmy Soni, a book about PayPal’s founding story — or my interview with the author and my post about scenius that touches on PayPal’s hiring methods, among other things.]

Proving Popperian Falsification

Karl Popper is often credited with the idea of falsification, namely that a hypothesis can never be confirmed but only ever disconfirmed. No number of spottings of white swans is sufficient to confirm the statement ‘all swans are white’, but a single sighting of a non-white swan is sufficient to disconfirm (falsify) it.

I had come this idea across a number of times, most notably in David Deutsch’s The Beginning of Infinity and in George Soros’ writings. While the idea of falsification is intuitively obvious, The Black Swan helped me gain deeper insights into a proof of the idea, which I detail here.

First, consider that the statement ‘all swans are white’ is logically equivalent to its contrapositive statement ‘all non-white objects are non-swans’ — which in turn can be rephrased as ‘the set of all non-white objects does not contain swans’.

For intuition, one can think of the contrapositive as a mathematical inequality: when both sides are multiplied by a negative number or when the reciprocal of both sides is taken (the or here is exclusive), the inequality sign is flipped. For instance, 5 > 3, but 1/5 < 1/3.

Hence, if it is true that the spotting of a white swan constitutes evidence for the validity of ‘all swans are white’, then it is also true that the spotting of a non-white non-swan (say, a red car) constitutes evidence for the validity of ‘all swans are white’. The latter is clearly erroneous, hence the Popperian idea of falsification is proven via reductio ad absurdum — QED.

Note how the above reasoning has not confirmed falsification itself, but disconfirmed its opposite — a proof by contradiction. Even falsification itself cannot be confirmed — this is akin to how a fallibilist must question fallibilism itself, or how a skeptical empiricist must doubt skeptical empiricism itself.

I would rather have questions that can’t be answered than answers that can’t be questioned.

— Richard Feynman

Kolmogorov Complexity

Suppose I send you a message of information value, say, one million bits, and you wish you further transmit this message to person X. If the characters in the message are perfectly random (such that the message makes no sense to a human), your transmitted message must also necessarily contain one million bits.

However, suppose now that the message I send you — again with a million bits — has the phrase ‘Black Swans are asymmetric’ typed out 50 times. In this case, your message to person X could simply type the phrase once and include a rule for repeating it 50 times. Hence, the message you transmit to person X contains much fewer than a million bits.

This phenomenon is termed Kolmogorov complexity, after Andrey Kolmogorov. The insights here are plentiful.

First, notice how Kolmogorov complexity is intensely dynamic, which means that an arbitrarily long, convoluted message (say, 200 pages long) that is seemingly random (high complexity) can, with the addition of a single suitable sentence, make complete sense.

This extra phrase may be, for example, a key to decrypt the message, or context that helps make sense of it. In such a case, complexity plummets instantly — and, somewhat counterintuitively, even though the extra sentence adds information (bits), it reduces the Kolmogorov complexity of the message as a whole.

This first point is similar to the idea of data compression.

Imagine six animated people having dinner around a table; they are deeply engrossed in a common discussion about, say, a person not there. During one moment of this discourse about Mr. X, I look across the table at my wife and wink. After dinner, you come up to me and say, “Nicholas, I saw you wink at Elaine. What did you tell her?”

I explain to you that we had dinner with Mr. X two nights before, at which time he explained that, contrary to __ he was in fact __, even though people thought __, but what he really decided was __ etc. Namely, 100,000 bits (or so) later, I am able to tell you what I communicated to my wife with 1 bit (I ask your forbearance with my assumption that a wink is 1 bit through the ether).

What is happening in this example is that the transmitter (me) and the receiver (Elaine) hold a common body of knowledge, and thus communication between us can be in shorthand. In this example, I fire a certain bit through the ether and it expands in her head, triggering much more information. When you ask me what I said, I am forced to deliver to you all 100,000 bits. I lose the 100,000-to-l data compression.

— Nicholas Negroponte, in Being Digital

Second, the parallels to computer code are plentiful. Consider how, in the case of the second message, a FOR loop can replace repeated PRINT functions, thus making the code succinct. In some sense, therefore, there exists a correspondence between Kolmogorov complexity and the maximal compactness of a computer program (an isomorphism, as GEB fans would call it).

Type I and II errors

“The power law means that differences between companies will dwarf the differences in roles inside companies.” Hence, participating in the ones that will create value is crucial. Put differently, when it comes to betting on outliers, mistakes of omission (type I) are much more expensive than mistakes of commission (type II).

The nature of the argument being made here is very similar to one that comes up often in math and physics:

• Mass of string << mass of weights in a pulley system

• Radius of earth >> height of a building

In such scenarios, the limiting case is often of great interest. The limit as x tends to infinity of (ln x / x) equals zero, for instance.

Connecting the dots, one can see that outlier bets premised on the power law distribution (0 to 1) are orthogonal to evolutionary biology (1 to n) — the former seeks to minimise Type II errors while the latter seeks to minimise Type I errors.

Natural selection among animals is incessant and merciless and has produced millions of species, all of whom adhere to this simple principle: Minimize the risk of committing type I errors to curtail the risk of injury or death, and learn to live with type II errors or foregone benefits.

— Pulak Prasad, in What I Learned About Investing from Darwin

Likewise for Black Swans — since they are so rare and impactful, Type I errors (omission) are costlier than Type II errors (commission).

Reverse Turkey

In some sense, connecting the dots with Zero To One, the reverse turkey idea is attempting an answer to the contrarian question, effectively saying: “Most people think Black Swan outliers can be safely ignored because they are not representative of the average, but the reality is that they drive the vast majority of outcomes in Extremistan.”

When betting that a Black Swan will occur, one is effectively being contrarian, risking a very-likely-but-small downside in pursuit of a highly-improbable-but-potentially-massive upside. Remember that a Black Swan is relative to expectations, so if a given event is to be a potential Black Swan, its complement (in set theory terms) must necessarily be “priced in” or “factored in”; hence, the non-occurence of the Black Swan does not create surprise, and therefore does not lead to a large downside. On the other hand, the occurence of the Black Swan does create surprise (by definition, since a Black Swan is relative to expectation), and hence promises a large upside if it materialises.

This framework supports Nero’s “bleed” strategy.

… Nero engaged in a strategy that he called “bleed.” You lose steadily, daily, for a long time, except when some event takes place for which you get paid disproportionately well. No single event can make you blow up, on the other hand—some changes in the world can produce extraordinarily large profits that pay back such bleed for years, sometimes decades, sometimes even centuries.

However, always betting that the Black Swan will occur effectively amounts to blind contrarianism — being contrarian just for the sake of opposing the crowds. Isn’t that simply a form of calibrated herd mentality (following the crowd but with a negative coefficient), as Patrick Collison suggests? This remains an open question for me, and thoughts would be very welcome.

One possible solution I can think of is that the Collison idea does not incorporate asymmetry of payoffs while the Taleb idea does.

However, there must be alignment between such a strategy and its practitioner.

…some business bets in which one wins big but infrequently, yet loses small but frequently, are worth making if others are suckers for them and if you have the personal and intellectual stamina. But you need such stamina. You also need to deal with people in your entourage heaping all manner of insult on you, much of it blatant.

People often accept that a financial strategy with a small chance of success is not necessarily a bad one as long as the success is large enough to justify it. For a spate of psychological reasons, however, people have difficulty carrying out such a strategy, simply because it requires a combination of belief, a capacity for delayed gratification, and the willingness to be spat upon by clients without blinking. And those who lose money for any reason start looking like guilty dogs, eliciting more scorn on the part of their entourage.

The nature of the referred-to stamina is itself interesting: “The main tragedy of the high impact-low probability event comes from the mismatch between the time taken to compensate someone and the time one needs to be comfortable that he is not making a bet against the rare event.”

Essentially, the contrarian view needs to be held for a long period of time, while the compensation — the “extraordinarily large profits that pay back such bleed for years, sometimes decades, sometimes even centuries” — is paid out in an extremely short period of time.

This connects back to the idea of minimising omission errors: since the compensation is paid out in an extremely short time period, it is of paramount importance that one participates during this time.

Ludic Fallacy

The ludic fallacy is when ideal, model games with odds that can be mathematically computed (e.g., blackjack) are used to learn about probabilities in the messy real world (e.g., financial markets).

…organized competitive fighting trains the athlete to focus on the game and, in order not to dissipate his concentration, to ignore the possibility of what is not specifically allowed by the rules, such as kicks to the groin, a surprise knife, et cetera. So those who win the gold medal might be precisely those who will be most vulnerable in real life.

Viewed from a different angle, then, the Black Swan idea is another solution to the contrarian question, effectively saying: “Most analysts focus on ideal, Platonic, precise-but-inaccurate probability calculations, but the reality is that while probabilities are hard to ascertain and susceptible to the ludic fallacy, payoffs can be estimated with a much lower error rate.”

Incremental Conditional Probabilities

For a normally distributed variable like expected lifespan, the older you grow, the lesser your incremental expected time to live. At birth, one might expect to live till the age of 80. At 80, one might expect to live another 5 years; at 85, another 2 years, and so on.

For a power-law distributed variable, on the other hand, the reverse is true. The better a startup is performing, the better it is expected to perform going forward. The more delayed a project already is, the longer it will take to complete going forward. This idea, which might be familiar as as the Lindy effect, supports the adage ‘average up your winners’.

Hofstadter’s Law: It always takes longer than you expect, even when you take into account Hofstadter’s Law.

— Douglas Hofstadter, in Gödel, Escher, Bach

Betting on Black Swans

Let me now present my understanding of the conditions under which it pays to bet on Black Swans (assuming the stamina condition is satisfied). Consider the concept of expected value: the probability multiplied by payoff, summed over all possible events.

I am skeptical about precise, numerical calculations of expected value — for instance, computing the expected value of a stock by estimating the probability-weighted bull, base, and bear scenarios — since these are susceptible to the ludic fallacy. Such an approach works when the odds are well-established and known, but that is hardly the case in many emergent domains.

Having said that, the non-numerical idea of expected value provides an interesting explanation for the payoffs of betting on Black Swans.

First, consider the trivial statement that as the extremity of an event increases, its probability decreases. However, the rate at which this occurs differs greatly depending on the nature of the distribution.

For a normally distributed variable (Gaussian/bell curve), the probability of extreme events declines at an exponentially increasing rate. The probability of a 4-sigma event is twice that of a 4.15-sigma event; the probability of a 20-sigma event is one trillion times that of a 21-sigma event!

On the other hand, a power law distribution is characterised by scale-invariance. In fact, the very name — ‘power’ in ‘power law’ — relates to the exponent in fractals, i.e., fractal dimensions (also called Hausdorff dimensions). Fractals are defined through recursion and scale-invariant structures. As a result, probabilities do not fall disproportionately for events with ever-increasing extremity.

In both cases, as extremity rises, probability falls (of course) — the difference is that this decrease in probability is disproportionate and exponential in a normal distribution but not in a power law distribution.

Thinking back to expected value,

• In a normal distribution, expected value falls as extremity of an event rises (since the decrease in probability offsets the increase in extreme payoffs)

• In a power law distribution, expected value rises as extremity of an event rises (since the increase in extreme payoffs offsets the decrease in probability)

This, then, is a slightly technical way of reasoning to illustrate the same idea: betting on outlier Black Swans is a favourable strategy in power law distributed systems, though not in normally distributed ones.

Worldviews

Optimism and pessimism are self-explanatory. A definite world is where one has firm convictions and systematic plans. An indefinite frame is one where no concrete measures are taken to transform the optimistic or pessimistic worldview into reality.

Since Black Swans are relative to expectation — what is a Black Swan for the hypothetical turkey is not a Black Swan for the butcher — definite optimists are well-prepared for outlier events, while indefinite optimists are exposed to negative Black Swans.

By the way, I hypothesise that these philosophical worldviews are linked to world orders (as described in Ray Dalio’s Principles For Dealing With The Changing World Order) — I hypothesise that definite optimism is linked to a favourable world order position (e.g., USA in the 1950s).

There are a whole host of ideas that I’ve skipped here for brevity’s sake: redundancy as a hedge against fragility, Popper’s fundamental unpredictability, barbell strategy, evidence of no disease ≠ no evidence of disease, the equivalence between predicting a random variable and guessing a nonrandom-but-unknown variable, and much more.

Feedback and reading recommendations are invited at malhar.manek@gmail.com

About an hour away — from the Bell Labs HQ at Murray Hill to Einstein Drive in Princeton — is another intellectual juggernaut: the Institute for Advanced Study. IAS was home to legends like John von Neumann, J. Robert Oppenheimer and John Nash. Albert Einstein and Kurt Gödel famously went on walks together. Even today, leading researchers like Edward Witten and Juan Maldacena are at IAS. In the words of a friend who is a physics PhD candidate, “IAS will set a problem and every other university will work on it”.

Musician Brian Eno calls this phenomenon “scenius”, or scene-genius. Throughout history, there have been numerous instances of scenius:

• Plato’s Academy (considered to be the world’s first university; see The School of Athens, featuring Plato, Aristotle, Socrates, Euclid, Pythagoras and others)

• RAND Corporation (“It attracted some of the best minds in mathematics, physics, political science, and economics. RAND may well have been the model for Isaac Asimov's Foundation series, about a RAND-like organization full of hyper-rational social scientists — psychohistorians — who are supposed to save the galaxy from chaos”; see Sylvia Nasar’s A Beautiful Mind)

• Fairchild Semiconductor (the future founders of Intel, Kleiner Perkins and others were part of the “traitorous eight” that founded Fairchild; see Sebastian Mallaby’s The Power Law)

• MIT Building 20 (Bose loudspeakers, LIGO gravitational wave antenna project, and Chomsky grammars all originated here; see Cal Newport’s Deep Work)

• Los Alamos (the Manhattan Project at Los Alamos created the world’s first atomic bomb; see Richard Feynman’s Surely You’re Joking Mr. Feynman)

• The “PayPal Mafia” (the founders and early investors in SpaceX, Tesla, Facebook, YouTube, LinkedIn and Palantir were all once at PayPal; see Jimmy Soni’s The Founders — or my interview with the author)

• Bureau of Municipal Research, New York (the trio of civil reformers, Allen, Bruère and Cleveland — ABC — who worked from 261 Broadway NYC and pioneered a scientific approach to government; see Robert Caro’s The Power Broker)

Even Warren Buffett recognises the phenomenon of scenius — Charlie Munger, Ajit Jain, Greg Abel and Buffett himself all lived in Omaha at some point. As he asks,

So what is going on? Is it Omaha’s water? Is it Omaha’s air? Is it some strange planetary phenomenon akin to that which has produced Jamaica’s sprinters, Kenya’s marathon runners, or Russia’s chess experts?

— Warren Buffett, in Berkshire Hathaway’s 2023 letter to shareholders

Let’s find out!

Valleius, the Roman philosopher, was the first to offer a theory for why geniuses often appeared, not as lonely giants, but in clusters in particular fields in particular cities. He was thinking of Plato and Aristotle, Pythagoras and Archimedes, and Aeschylus, Euripides, Sophocles, and Aristophanes, but there are many later examples as well, including Newton and Locke, or Freud, Jung, and Adler.

He speculated that creative geniuses inspired envy as well as emulation and attracted younger men who were motivated to complete and recast the original contribution.

— Sylvia Nasar, in A Beautiful Mind

In this spirit, here are some of characteristics that I’ve seen recur in numerous instances of scenius.

Combining Theory and Practice

At Bell Labs, the man most responsible for the culture of creativity was Mervin Kelly … His fundamental belief was that an “institute of creative technology” like his own needed a “critical mass” of talented people to foster a busy exchange of ideas.

But innovation required much more than that. Mr. Kelly was convinced that physical proximity was everything; phone calls alone wouldn’t do. Quite intentionally, Bell Labs housed thinkers and doers under one roof. Purposefully mixed together on the transistor project were physicists, metallurgists and electrical engineers; side by side were specialists in theory, experimentation and manufacturing.

Like an able concert hall conductor, he sought a harmony, and sometimes a tension, between scientific disciplines; between researchers and developers; and between soloists and groups.

— An article by Jon Gertner in the New York Times

Similarly, Elon Musk fused the design and engineering aspects of his rockets and cars.

Musk restructured the company so that there was not a separate engineering department. Instead, engineers would team up with product managers. It was a philosophy that he would carry through to Tesla, SpaceX, and then Twitter. Separating the design of a product from its engineering was a recipe for dysfunction. Designers had to feel the immediate pain if something they devised was hard to engineer.

— Walter Isaacson, in Elon Musk

Enabling Serendipity, or Expanding the Luck Surface Area

You know how Richard Feynman was once recruited by the University of Chicago, which offered to double his salary or something like that. He was asked, “Why wouldn’t you leave Caltech and take this offer?” and I think—to paraphrase—he said, “At Caltech, if I moved a meter or two, I would be in collision with somebody who will excite my interest.”

— Ahmed Zewail (1946-2016), Nobel Laureate

In fact, this was part of the deliberate design of Bell Labs’ architecture.

Members of the technical staff would often have both laboratories and small offices—but these might be in different corridors, therefore making it necessary to walk between the two, and all but assuring a chance encounter or two with a colleague during the commute.

By the same token, the long corridor for the wing that would house many of the physics researchers was intentionally made to be seven hundred feet in length. It was so long that to look down it from one end was to see the other end disappear at a vanishing point.

Traveling its length without encountering a number of acquaintances, problems, diversions, and ideas would be almost impossible. Then again, that was the point. Walking down that impossibly long tiled corridor, a scientist on his way to lunch in the Murray Hill cafeteria was like a magnet rolling past iron filings.

— Jon Gertner, in The Idea Factory

And, indeed, at RAND Corporation as well, where “graduate students rubbed shoulders with full professors in a way unimaginable in most academic departments.”

There were no afternoon teas, formal seminars, or faculty meetings at RAND. Unlike the physicists and engineers, the mathematicians usually worked alone. The idea was that they would work on their own ideas but would help solve the myriad problems encountered by researchers, picking up problems to solve as the spirit moved them. People would drift into each other's offices or, more frequently, simply stop to chat in the corridors near the coffee stations. The grids and courtyards of RAND’s permanent headquarters were designed … by John Williams, as it happens, “to maximize chance meetings”.

— Sylvia Nasar, in A Beautiful Mind

Transcending Disciplinary Boundaries

The result [of using MIT’s Building 20 as an overflow space] was that a mismatch of different departments — from nuclear science to linguistics to electronics — shared the low-slung building alongside more esoteric tenants such as a machine shop and a piano repair facility.

Because the building was cheaply constructed, these groups felt free to rearrange space as needed. Walls and floors could be shifted and equipment bolted to the beams. In recounting the story of Jerrold Zacharias’s work on the first atomic clock, [a New Yorker article] points to the importance of his ability to remove two floors from his Building 20 lab so he could install the three-story cylinder needed for his experimental apparatus.

In MIT lore, it’s generally believed that this haphazard combination of different disciplines, thrown together in a large reconfigurable building, led to chance encounters and a spirit of inventiveness that generated breakthroughs at a fast pace, innovating topics as diverse as Chomsky grammars, Loran navigational radars, and video games, all within the same productive postwar decades.

— Cal Newport, in Deep Work

It is also what made Florence the epicentre of Renaissance art.

This mixing of ideas [in Florence] from different disciplines became the norm as people of diverse talents intermingled. Silk makers worked with goldbeaters to create enchanted fashions. Architects and artists developed the science of perspective. Wood-carvers worked with architects to adorn the city’s 108 churches. Shops became studios. Merchants became financiers. Artisans became artists…

Florence’s festive culture was spiced by the ability to inspire those with creative minds to combine ideas from disparate disciplines. In narrow streets, cloth dyers worked next to goldbeaters next to lens crafters, and during their breaks they went to the piazza to engage in animated discussions.

At the Pollaiuolo workshop, anatomy was being studied so that the young sculptors and painters could better understand the human form. Artists learned the science of perspective and how angles of light produce shadows and the perception of depth. The culture rewarded, above all, those who mastered and mixed different disciplines.

— Walter Isaacson, in Leonardo da Vinci

Or consider DeepMind (now part of Google), which made breakthroughs in protein folding, chess, and Go.

John Jumper, who currently leads the AlphaFold team and was first-author on DeepMind’s 2021 Nature paper, studied physics at Cambridge and worked as Scientific Associate at D. E. Shaw Research before completing his graduate work in theoretical chemistry at the University of Chicago. Demis Hassabis studied computer science at Cambridge, pioneered AI-based videogame design at Lionhead Studios, and completed his graduate studies in cognition and neuroscience at UCL, then MIT, then Harvard.

Once again, we see a spark at the confluence of disciplines and backgrounds. With Jumper and co.’s experience in computation and biology, and Hassabis and co.’s experience building AI for games, the ingredients for AlphaFold are ready. [emphasis added]

— in his write-up on AlphaFold

Hiring

Since scenius is, by definition, the coming together of bright minds working on a common mission, it is imperative to understand hiring. How are employees selected? How do the early hires represent the culture embodied by the organisation as a whole?

The best way to understand this is by studying the stories of those who did it best.

At PayPal, Neal Stephenson’s Cryptonomicon was required reading — if you enjoyed it, you might be a good fit for the culture. Interview questions to prospective hires included mathematical puzzles.

Imagine you have two ropes of variable density. If you set either rope on fire, despite burning at varying speeds, it will be entirely gone in one hour. Using the two ropes, measure exactly 45 minutes…

There’s a perfectly round table of indeterminate length, and you don’t know the length in advance. Two players have a bag of quarters of infinite depth. Each player can place a coin in the table, and they can touch but not overlap. The last person who puts a coin down on the table and fills it up wins the game. Is there a way to guarantee victory in advance, and does that involve going first or second?

— Jimmy Soni, in The Founders

D. E. Shaw & Co. is famous for asking Fermi estimate questions in their interviews. Given that Jeff Bezos worked there before leaving to start Amazon, it isn’t surprising that they, too, pose such mind teasers.

How many fax machines are in the United States? (D. E. Shaw & Co.)

How many gas stations are in the United States? (Amazon)

— Brad Stone, in The Everything Store

In an early example of “feeder schools”, Bell Labs used to hire Robert Millikan’s best graduate students at the University of Chicago.

Jewett [of Bell Labs] kept writing to Harvey Fletcher, Millikan’s former graduate student who was now in Salt Lake City, sending him every spring for five consecutive years a polite and persuasive invitation to join AT&T. In 1916, Fletcher finally agreed to leave Brigham Young and come work for Jewett.

Millikan, meanwhile, didn’t stop serving as the link between his Chicago graduates and his old friend. In late 1917, responding to an offer from Jewett for $2,100 a year, Mervin Kelly, now done counting oil drops, decided that he would come to New York City, too.

— Jon Gertner, in The Idea Factory

Here’s how the great John D. Rockefeller Sr. went about building the Rockefeller Institute for Medical Research.

Rockefeller placed a premium on recruiting the best people for leading positions. “John, we have money,” he told his son, “but it will have value for mankind only as we can find able men with ideas, imagination and courage to put it into productive use.”

That Rockefeller placed scientists, not lay trustees, in charge of expenditures was thought revolutionary. This was the institute’s secret formula: gather great minds, liberate them from petty cares, and let them chase intellectual chimeras without pressure or meddling. If the founders created an atmosphere conducive to creativity, things would, presumably, happen.

— Ron Chernow, in Titan

Autonomy

What do you do after you’ve put candidates through a labyrinth of Fermi estimates, math riddles and 1,000 page sci-fi readings and cherry-picked the best?

The scenius answer: leave them alone.

If Shannon had peculiar work habits before the publication of his information theory, his growing reputation granted him the license to indulge those peculiarities without reservation. After 1948, the Bell Labs bureaucracy could not touch him—which was precisely as Shannon preferred it.

Henry Pollak, director of Bell Labs’ Mathematics Division, spoke for a generation of Bell leaders when he declared that Shannon “had earned the right to be non-productive.”

Shannon arrived at the Murray Hill office late, if at all, and often spent the day absorbed in games of chess and hex in the common areas. When not besting his colleagues in board games, he could be found piloting a unicycle through Bell Labs’ narrow passageways, occasionally while juggling; sometimes he would pogo-stick his way around the Bell Labs campus, much to the consternation, we imagine, of the people who signed his paychecks.

— Jimmy Soni and Rob Goodman, in A Mind At Play

A strikingly similar environment was at RAND Corporation.

All but one or two of the mathematicians, including Nash, came to work in short-sleeved shirts. Appearances were so casual that one mathematician, who found it all very déclassé, felt obliged to rebel by wearing a three-piece suit and a tie to the office every day…

The mathematicians were, as usual, the freest spirits. They had no set hours. If they wanted to come into their offices at 3:00 A.M., fine. Shapley, who had come back from Princeton for the summer and continued to insist on the sanctity of his sleep cycle, was rarely seen before midafternoon. Another man, an electrical engineer named Hastings, typically slept in the “shop” next to his beloved computer.

Lunches were long, much to the annoyance of RAND’s engineers, who prided themselves on sticking to a more respectable routine. The mathematicians mostly took their bag lunches to a conference room and pulled out chessboards. They invariably played Kriegspiel, usually in total silence, occasionally punctuated by a wrathful outburst from Shapley, who frequently lost his temper over an umpire’s or opponent’s error.

Here’s what an early PayPal employee said about the culture.

[PayPal] hired really good people, gave them a lot of trust, and so people ran at their own pace, just made sure that they checkpointed to make sure we were in sync occasionally. And then we would just keep on running. So they got the best out of some very, very smart people.

— Santosh Janardhan, in The Founders

For those interested in books about scenius, I recommend Sylvia Nasar’s A Beautiful Mind (RAND Corporation and Institute for Advanced Study), Sebastian Mallaby’s The Power Law (Silicon Valley), Jimmy Soni’s The Founders (PayPal), and Jon Gertner’s The Idea Factory (Bell Labs).

There are also some wonderful articles about scenius. My favourites are these ones by Kevin Kelly, Packy McCormick and Infinite Loops.

This essay has wonderful insights from Abraham Flexner, the founding director of IAS.

Feedback and reading recommendations are invited at malhar.manek@gmail.com