Multi-Disciplinary Reading - Book Reviews

[Adhiraj]

Moonwalking with Einstein
Joshua Foer (2011)

I had always read the stories of humans blessed with impeccable memory and it had made me believed that they have had some serious genetic advantage in life. I now realize that I got it all wrong. I wish that I had read this book some time ago. A good memory is more a result of one’s technique rather than genetics.

I read this book with another similar book called Unlimited Memory by Kevin Horsley a few months ago which is also worth a read and throws some light on absolutely useful memory techniques.

These days, our memory is externalized such that unlike historical times such that we don’t need to remember vast amounts of information. But as is the case with knowledge, you need knowledge to grow knowledge. Its just like compounding money. Retaining information is essential to making useful insights. Memory is important in this age, well much more important than many of us have been led to believe.

The book has a theory part and an autobiographical part in which the author tells us about his journey into the US memory championship. Some of my insights/notes from this book are

• Historically, traditions often focused on memory techniques to pass on folklore and religious scriptures in absence of writing. But somewhere in the past few centuries, memory traditions have taken a backseat.
• We might be bad at remembering words or sounds but are great at remembering images. That is why we forget names but recognize faces.
• To remember more, one must take a fact and put it in a web of associations, analogies, feelings, distinct images in such a way that it is intertwined with the information you know. Good memory skills work in connecting the unknown to the known.
• Our brain is a great filtering mechanism. Any information not useful will slowly wither away. That is why skills are lost over time if not practiced. It’s probably an evolutionary tool to keep us alive.
• But all memories are stored somewhere. They are not lost but rather inaccessible. They are just lost in the background over time waiting for the right cue to bring it back which rarely arrives. Somewhere in the mind, there’s a trace of everything you have ever seen.
• Monotony collapses time, Novelty unfolds it. Time seems to pass faster as we grow older because we have fewer of new experiences.
• Our brains remember distinct memories much better because those memories have no rivals. We don’t remember the lunches we ate because they are not distinct and similar to all other lunches. Our brain remembers distinct events much more sharply than normal events. To remember something, make it absolutely distinct from everything else.
• Memory making is an act of creativity. The more creative you can get with information, the better it sticks.
• The book also talked about the curve of forgetting and the role of repeated repetition in memory-making.
• The man who remembered everything like a photograph(he was using similar memory techniques but doing it unconsciously) was unable to hold on to any job or work in real life. Almost all similar savants end up like this. Our brains are efficient because of their ability to forget stuff and focus on important things. Forgetting makes us human. No one would like to drown in a sea of useless data.
• Memory masters use techniques such as memory palace, mnemonic system, chunking, visualization, etc. Memory palace is the most common method. They are a little difficult to explain here but worth a read.

There is a lot more in this book, especially in the theory part which I have missed.

Joshua Foer’s narrative swings back and forth from theory of memory to his practice in an attempt to compete and win at the US memory championship. He talks about his chance encounter with certain memory contestants and his stint in memory competitions who eventually become his mentors. He trains for less than a year and wins the US memory championship. And he was not blessed with a good memory but was like any layman.

This book was one of the most enlightening and fun reads I have had in a long time. And made me understand to view information in a way that would help me in the future while learning new stuff. Some people might not like this book as much as I did. Memory is something I have been absolutely curious about for the past year and reading this book was a delight.
9/10

[phreakv6]

Capital Returns, Marathon Asset Management, 2015 - This is a collection of investment reports by Marathon’s portfolio managers between the years 2002 and 2015. Most (> 50%) of the letters are focused on the capital cycle analysis which is the phenomenon of excess profits driving excess capital into a sector thereby driving down the returns for everyone leading to a mean reversion and the idea that the best time to invest in that sector/country/economy then would be when capital is being withdrawn due to drying down of the profit pool leading to consolidations and liquidation of assets.

The reports are scathing on investment managers and PE firms for their proclivity to push companies to expand and then financing the same at the peak of the cycle earning fee income with scant regard to returns. It is also equally scathing on managements for value-destroying M&As driven by equity dilutions and buybacks at the peak of the cycle. Banks and lending businesses in general also get their fair share of brickbats, along with brokerages and their short-sighted research analysts and what I loved about all this was that it was written with a lot of specific examples and not in retrospect either while maintaining a consistency of opinion and a long-term focus across years. The central banks and politicians are not spared either with the lower interest rates prolonging the fate of the living dead questioning the very basis of capitalism.

Some parts I liked (paraphrased for brevity)

• High current profitability leads to overconfidence among managers who confuse benign industry conditions to their own skill - this is encouraged by media looking for corporate heroes

• Neither the M&A banker nor the brokerage analysts have much interest in long-term outcomes

• Delay between investment and new production capacity means supply changes are lumpy (cobweb effect in economics)

• Last commodity supercycle between 2002-2011 was driven by China’s investment heavy economy - as commodity prices rose, profitability of mining companies took off

• There is a inverse relationship between capex and investment returns (impact could last upto 5 years)
• combination of overconfidence, base-rate neglect, cognitive dissonance, narrow-framing and extrapolation drive the capital cycle anomalies

• co-operation in basic industries is crucial for shareholder value creation (look out for next outbreak of peace in competitive fronts)

• imposition of exit barriers can lead to survival of the unfittest

• Large number of IPOs and high M&A activity in any sector tend to occur in the later stages of the capital cycle

• Easier in a consolidated market to premiumize as having high volumes allows for wider price ranges

• There is no cure for high prices like high prices (peak oil)

• The whole industry is justifying higher investments based on inflated expectations of future oil prices (on rising oil investments in 2012)

• Mispricing within the growth stocks - Underestimation of the durability of the moat and underappreciation of the scale and scope of addressable market (value in growth)

• Reason why corporate profits lags GDP - Profitability is driven by favorable supply-side than by high rates of demand growth

• No correlation between long-term GDP growth and equity market return - China is a classic eg. with real equity return being negative despite stellar growth. Investors should not expect earnings to grow along with economy

• Double agents - When customer is not involved in purchasing decision, higher prices can be used to bribe the purchasing agent and can result in higher profit margins and sales volumes (Any business where agent gets between customer and producer)

• New entrants will struggle in a business with thousands of products of low volume - such markets make it difficult for new entrants to compete (Medical devices for eg.)

• High organic returns can be diluted quickly by poorly conceived investment decision and ill-timed buybacks

• When one company decides that buybacks are the thing to do, its competitors will play the game too. Competitors also raise capital at the same time as they don’t want to be left out (of the funding advantage)

• “Our job here is to create goodwill and not pay other people for goodwill” - (Rupert, CEO of Richemont)

• Equity is always the most expensive way to pay (Rupert)

• As banks hold onto less of the debt that they originate, they are bound to have less concern about longer-term credit quality. originate-then-distribute model is leading to a decline in quality of lending

• Moral hazard - the ability to take risk at other people’s expense

• Bank was borrowing short and lending long exploiting the latest financial innovations (a.k.a pass-the-hot-potato)

• Innovation in capital markets and the pursuit of fee-driven approaches has shifted risk to those least capable of evaluating it

• Deadly sins of banking - imprudent asset liability mismatches, supporting such mismatches by clients, lending to “can’t pay, won’t pay” types, reaching for growth in unfamiliar areas, off-balance sheet lending, getting sucked into virtuous/vicious cycle dynamics

• Economic recession is like a forest fire that destroys the deadwood and weaker trees so healthy young plants can grow and prosper. ultra-low interest rates prevent these and allow corporate zombies to continue limping

• Determination of the wealthy to earn somewhat more than risk-free rate which are near nothing will do more to restore equality than wealth taxes (fool and his money…)

The book closes with a primer on how the Chinese economy functions - with its investment led growth and supply-side excesses which kill profitability for everyone and how businesses aren’t allowed to die (exit barriers) and carving out of businesses from state-owned firms for public listing and manipulation of books and the difficulty to make returns. The final section was satirical but bit unfunny for my tastes (Marathon analysts aren’t Vonnegut) and can be comfortably skipped but the rest of the book was a calming read espousing the virtues of a long-term approach keeping the noise out. 9/10

[Akshay_Lulla]

Brother where did you order this book from? I’d love to keep a physical copy of this book. It’s an amazing book which requires a read once per year.

[raj1968]

Capital Returns: Investing Through the Capital Cycle: A Money Manager’s Reports

[Ansh_Gupta]

The Psychology of Money is a pretty interesting read, it throws light on the behavioral aspects of investing. The author also talks about how hard it is to generate an alpha in the stock market, not just with respect to the investing acumen but behaviorally too. Would rate the book 9/10

Summarizing it below: [most of the quotes are verbatim]
(sorry for the poor formatting, had originally made the notes in Microsoft OneNote)

	• The premise of this book is that doing well with money has a little to do with how smart you are and a lot to do with how you behave. And behavior is hard to teach, even to really smart people.
	• Financial success is not a hard science. It’s a soft skill, where how you behave is more important than what you know. I call this soft skill the psychology of money.
	• We all think we know how the world works. But we’ve all only experienced a tiny sliver of it. As investor Michael Batnick says, “some lessons have to be experienced before they can be understood.” We are all victims, in different ways, to that truth.
	• If you happened to grow up when the stock market was strong, you invested more of your money in stocks later in life compared to those who grew up when stocks were weak. The economists wrote: “Our findings suggest that individual investors’ willingness to bear risk depends on personal history.”
	• And that idea—“What you’re doing seems crazy but I kind of understand why you’re doing it.”—uncovers the root of many of our financial decisions.
	• It should surprise no one that many of us are bad at saving and investing for retirement. We’re not crazy. We’re all just newbies. Same for index funds, which are less than 50 years old. And hedge funds, which didn’t take off until the last 25 years.
	• Luck and risk are both the reality that every outcome in life is guided by forces other than individual effort. They are so similar that you can’t believe in one without equally respecting the other. They both happen because the world is too complex to allow 100% of your actions to dictate 100% of your outcomes. They are driven by the same thing: You are one person in a game with seven billion other people and infinite moving parts. The accidental impact of actions outside of your control can be more consequential than the ones you consciously take.
	• For every Bill Gates there is a Kent Evans who was just as skilled and driven but ended up on the other side of life roulette.
	• We similarly think Mark Zuckerberg is a genius for turning down Yahoo!’s 2006 $1 billion offer to buy his company. He saw the future and stuck to his guns. But people criticize Yahoo! with as much passion for turning down its own big buyout offer from Microsoft—those fools should have cashed out while they could! What is the lesson for entrepreneurs here? I have no idea, because risk and luck are so hard to pin down.
	• The best (and worst) managers drive their employees as hard as they can. “The customer is always right” and “customers don’t know what they want” are both accepted business wisdom. The line between “inspiringly bold” and “foolishly reckless” can be a millimeter thick and only visible with hindsight. Risk and luck are doppelgangers.
	• More important is that as much as we recognize the role of luck in success, the role of risk means we should forgive ourselves and leave room for understanding when judging failures. Nothing is as good or as bad as it seems.
	• The hardest financial skill is getting the goalpost to stop moving.
	Modern capitalism is a pro at two things: generating wealth and generating envy. Perhaps they go hand in hand;
	wanting to surpass your peers can be the fuel of hard work. But life isn’t any fun without a sense of enough. Happiness, as it’s said, is just results minus expectations.
	• $81.5 billion of Warren Buffett’s $84.5 billion net worth came after his 65th birthday. Our minds are not built to handle such absurdities.
	As I write this Warren Buffett’s net worth is $84.5 billion. Of that, $84.2 billion was accumulated after his 50th birthday. $81.5 billion came after he qualified for Social Security, in his mid-60s. Warren Buffett is a phenomenal investor. But you miss a key point if you attach all of his success to investing acumen. The real key to his success is that he’s been a phenomenal investor for three quarters of a century. Had he started investing in his 30s and retired in his 60s, few people would have ever heard of him.
	• The counterintuitive nature of compounding leads even the smartest of us to overlook its power. In 2004 Bill Gates criticized the new Gmail, wondering why anyone would need a gigabyte of storage. Author Steven Levy wrote, “Despite his currency with cutting-edge technologies, his mentality was anchored in the old paradigm of storage being a commodity that must be conserved.” You never get accustomed to how quickly things can grow.
	• But good investing isn’t necessarily about earning the highest returns, because the highest returns tend to be oneoff hits that can’t be repeated. It’s about earning pretty good returns that you can stick with and which can be repeated for the longest period of time. That’s when compounding runs wild.
	• Getting money is one thing. Keeping it is another.
	The Forbes 400 list of richest Americans has, on average, roughly 20% turnover per decade for causes that don’t have to do with death or transferring money to another family member.Capitalism is hard. But part of the reason this happens is because getting money and keeping money are two different skills.
	• Getting money requires taking risks, being optimistic, and putting yourself out there. But keeping money requires the opposite of taking risk. It requires humility, and fear that what you’ve made can be taken away from you just as fast. It requires frugality and an acceptance that at least some of what you’ve made is attributable to luck, so past success can’t be relied upon to repeat indefinitely.
	• But 40 years ago there was a third member of the group, Rick Guerin. Warren, Charlie, and Rick made investments together and interviewed business managers together. Then Rick kind of disappeared, at least relative to Buffett and Munger’s success. Investor Mohnish Pabrai once asked Buffett what happened to Rick.
	Mohnish recalled: [Warren said] “Charlie and I always knew that we would become incredibly wealthy. We were not in a hurry to get wealthy; we knew it would happen. Rick was just as smart as us, but he was in a hurry.” What happened was that in the 1973–1974 downturn, Rick was levered with margin loans. And the stock market went down almost 70% in those two years, so he got margin calls. He sold his Berkshire stock to Warren —Warren actually said “I bought Rick’s Berkshire stock”—at under $40 apiece. Rick was forced to sell because he was levered. Charlie, Warren, and Rick were equally skilled at getting wealthy. But Warren and Charlie had the added skill of staying wealthy.
	• Nassim Taleb put it this way: “Having an ‘edge’ and surviving are two different things: the first requires the second. You need to avoid ruin. At all costs.”
	• Anything that is huge, profitable, famous, or influential is the result of a tail event—an outlying one-in thousands or millions event. And most of our attention goes to things that are huge, profitable, famous, or influential. When most of what we pay attention to is the result of a tail, it’s easy to underestimate how rare and powerful they are. Some tail-driven industries are obvious. Take venture capital. If a VC makes 50 investments they likely expect half of them to fail, 10 to do pretty well, and one or two to be bonanzas that drive 100% of the fund’s returns. Investment firm Correlation Ventures once crunched the numbers, 20 Out of more than 21,000 venture financings from 2004 to 2014: 65% lost money. Two and a half percent of investments made 10x–20x.
	One percent made more than a 20x return. Half a percent—about 100 companies out of 21,000—earned 50x or more. That’s where the majority of the industry’s returns come
	• Not only do a few companies account for most of the market’s return, but within those companies are even more tail events.
	• In 2018, Amazon drove 6% of the S&P 500’s returns. And Amazon’s growth is almost entirely due to Prime and Amazon Web Services, which itself are tail events in a company that has experimented with hundreds of products, from the Fire Phone to travel agencies.
	• Apple was responsible for almost 7% of the index’s returns in 2018. And it is driven overwhelmingly by the iPhone, which in the world of tech products is as tail-y as tails get.
	And who’s working at these companies? Google’s hiring acceptance rate is 0.2%, Facebook’s is 0.1%, Apple’s is about 2%.So the people working on these tail projects that drive tail returns have tail careers.
	• Peter Lynch is one of the best investors of our time. “If you’re terrific in this business, you’re right six times out of 10,” he once said. There are fields where you must be perfect every time. Flying a plane, for example. Then there are fields where you want to be at least pretty good nearly all the time. A restaurant chef, let’s say.
	Investing, business, and finance are just not like these fields. Something I’ve learned from both investors and entrepreneurs is that no one makes good decisions all the time.
	• The most impressive people are packed full of horrendous ideas that are often acted upon. Take Amazon. It’s not intuitive to think a failed product launch at a major company would be normal and fine. Intuitively, you’d think the CEO should apologize to shareholders. But CEO Jeff Bezos said shortly after the disastrous launch of the company’s Fire Phone: If you think that’s a big failure, we’re working on much bigger failures right now. I am not kidding. Some of them are going to make the Fire Phone look like a tiny little blip. It’s OK for Amazon to lose a lot of money on the Fire Phone because it will be offset by something like Amazon Web Services that earns tens of billions of dollars. Tails to the rescue.
	• At the Berkshire Hathaway shareholder meeting in 2013 Warren Buffett said he’s owned 400 to 500 stocks during his life and made most of his money on 10 of them. Charlie Munger followed up: “If you remove just a few of Berkshire’s top investments, its long-term track record is pretty average.”
	• “It’s not whether you’re right or wrong that’s important,” George Soros once said, “but how much money you make when you’re right and how much you lose when you’re wrong.” You can be wrong half the time and still make a fortune.
	• There are 100 billion planets in our galaxy and only one, as far as we know, with intelligent life. The fact that you are reading this book is the result of the longest tail you can imagine.
	• THE HIGHEST FORM of wealth is the ability to wake up every morning and say, “I can do whatever I want today.”
	• The most powerful common denominator of happiness was simple. Campbell summed it up: Having a strong sense of controlling one’s life is a more dependable predictor of positive feelings of wellbeing than any of the objective conditions of life we have considered. More than your salary. More than the size of your house. More than the prestige of your job. Control over doing what you want, when you want to, with the people you want to,
	is the broadest lifestyle variable that makes people happy.
	• A small amount of wealth means the ability to take a few days off work when you’re sick without breaking the bank. Gaining that ability is huge if you don’t have it. A bit more means waiting for a good job to come around after you get laid off, rather than having to take the first one you find. That can be life changing. Six months’ emergency expenses means not being terrified of your boss, because you know you won’t be ruined if you have to take some time off to find a new job. More still means the ability to take a job with lower pay but flexible hours. Maybe one with a shorter commute. Or being able to deal with a medical emergency without the added burden of worrying about how you’ll pay for it. Then there’s retiring when you want to, instead of when you need to. Using your money to buy time and options has a lifestyle benefit few luxury goods can compete with.
	• Throughout college I wanted to be an investment banker. There was only one reason why: they made a lot of
	money. That was the only drive, and one I was 100% positive would make me happier once I got it. I scored a summer internship at an investment bank in Los Angeles in my junior year, and thought I won the career lottery. This is all I ever wanted. On my first day I realized why investment bankers make a lot of money: They work longer and more controlled hours than I knew humans could handle. Actually, most can’t handle it. Going home before midnight was considered a luxury, and there was a saying in the office: “If you don’t come to work on Saturday, don’t bother coming back on Sunday.” The job was intellectually stimulating, paid well, and made me feel important. But every waking second of my time became a slave to my boss’s demands, which was enough to turn it into one of the most miserable experiences of my life. It was a four-month internship. I lasted a month.
	• The hardest thing about this was that I loved the work. And I wanted to work hard. But doing something you love on a schedule you can’t control, can feel the same as doing something you hate.
	• Part of what’s happened here is that we’ve used our greater wealth to buy bigger and better stuff. But we’ve simultaneously given up more control over our time. At best, those things cancel each other out.
	• 38% of jobs are now designated as “managers, officials, and professionals.” These are decision-making jobs. Another 41% are service jobs that often rely on your thoughts as much as your actions. More of us have jobs that look closer to Rockefeller than a typical 1950s manufacturing worker, which means our days don’t end when we clock out and leave the factory. We’re constantly working in our heads, which means it feels like work never ends.
	• Compared to generations prior, control over your time has diminished. And since controlling your time is such a key happiness influencer, we shouldn’t be surprised that people don’t feel much happier even though we are, on average, richer than ever.
	• Take it from those who have lived through everything: Controlling your time is the highest dividend money pays.
	• The letter I wrote after my son was born said, “You might think you want an expensive car, a fancy watch, and a huge house. But I’m telling you, you don’t. What you want is respect and admiration from other people, and you think having expensive stuff will bring it. It almost never does—especially from the people you want to respect and admire you.”
	• Someone driving a $100,000 car might be wealthy. But the only data point you have about their wealth is that they have $100,000 less than they did before they bought the car (or $100,000 more in debt). That’s all you know about them. We tend to judge wealth by what we see, because that’s the information we have in front of us. We can’t see people’s bank accounts or brokerage statements. So we rely on outward appearances to gauge financial success. Cars. Homes. Instagram photos.
	• When most people say they want to be a millionaire, what they might actually mean is “I’d like to spend a million dollars.” And that is literally the opposite of being a millionaire.
	• Exercise is like being rich. You think, “I did the work and I now deserve to treat myself to a big meal.” Wealth is turning down that treat meal and actually burning net calories. It’s hard, and requires self-control. But it creates a gap between what you could do and what you choose to do that accrues to you over time.
	• Do not aim to be coldly rational when making financial decisions. Aim to just be pretty reasonable. Reasonable is more realistic and you have a better chance of sticking with it for the long run, which is what matters most when managing money.
	• One-degree increase in body temperature has been shown to slow the replication rate of some viruses by a factor of 200.
	“Fevers turn on the body’s immune system. They help the body fight infection. Normal fevers between 100° and 104° f are good for sick children.”But that’s where the science ends and reality takes over. Fever is almost universally seen as a bad thing. They’re treated with drugs like Tylenol to reduce them as quickly as they appear.
	Despite millions of years of evolution as a defense mechanism, no parent, no patient, few doctors, and certainly no drug company views fever as anything but a misfortune that should be eliminated.
	It may be rational to want a fever if you have an infection. But it’s not reasonable. That philosophy—aiming to be reasonable instead of rational—is one more people should consider when making decisions with their money.
	• A rational investor makes decisions based on numeric facts. A reasonable investor makes them in a conference room surrounded by co-workers you want to think highly of you, with a spouse you don’t want to let down, or judged against the silly but realistic competitors that are your brother-in-law, your neighbor, and your own personal doubts. Investing has a social component that’s often ignored when viewed through a strictly financial lens.
	• Investing is not a hard science. It’s a massive group of people making imperfect decisions with limited information about things that will have a massive impact on their wellbeing, which can make even smart people nervous, greedy and paranoid.
	• A forecaster who assumes the worst (and best) events of the past will match the worst (and best) events of the future is not following history; they’re accidentally assuming that the history of unprecedented events doesn’t apply to the future.
	• Nassim Taleb writes in his book Fooled By Randomness: In Pharaonic Egypt … scribes tracked the high-water mark of the Nile and used it as an estimate for a future worst-case scenario. The same can be seen in the Fukushima nuclear reactor, which experienced a catastrophic failure in 2011 when a tsunami struck. It had been built to withstand the worst past historical earthquake, with the builders not imagining much worse—and not thinking that the worst past event had to be a surprise, as it had no precedent.
	This is not a failure of analysis. It’s a failure of imagination. Realizing the future might not look anything like the past is a special kind of skill that is not generally looked highly upon by the financial forecasting community.
	• At a 2017 dinner I attended in New York, Daniel Kahneman was asked how investors should respond when our forecasts are wrong. He said: Whenever we are surprised by something, even if we admit that we made a mistake, we say, ‘Oh I’ll never make that mistake again.’ But, in fact, what you should learn when you make a mistake because you did not anticipate something is that the world is difficult to anticipate. That’s the correct lesson to learn from surprises: that the world is surprising.
	• There’s a common phrase in investing, usually used mockingly, that “It’s different this time.” If you need to rebut someone who’s predicting the future won’t perfectly mirror the past, say, “Oh, so you think it’s different this time?” and drop the mic.
	• “The purpose of the margin of safety is to render the forecast unnecessary.”
	People underestimate the need for room for error in almost everything they do that involves money: Stock analysts give their clients price targets, not price ranges. Economic forecasters predict things with precise figures; rarely broad probabilities. The pundit who speaks in unshakable certainties will gain a larger following than the one who says “We can’t know for sure,” and speaks in probabilities.
	• It is easy to underestimate what a 30% decline does to your psyche. Your confidence may become shot at the very moment opportunity is at its highest. You—or your spouse—may decide it’s time for a new plan, or new career.
	• I know several investors who quit after losses because they were exhausted. Physically exhausted.
	Spreadsheets are good at telling you when the numbers do or don’t add up. They’re not good at modeling how you’ll feel when you tuck your kids in at night wondering if the investment decisions you’ve made were a mistake that will hurt their future.
	• You have to take risk to get ahead, but no risk that can wipe you out is ever worth taking. The odds are in your favor when playing Russian roulette. But the downside is not worth the potential upside.
	• A good rule of thumb for a lot of things in life is that everything that can break will eventually break. So if many things rely on one thing working, and that thing breaks, you are counting the days to catastrophe. That’s a single point of failure.
	• Predicting what you’ll use your savings for assumes you live in a world where you know exactly what your future expenses will be, which no one does. I save a lot, and I have no idea what I’ll use the savings for in the future.
	• Long-term financial planning is essential. But things change— both the world around you, and your own goals and desires. It is one thing to say, “We don’t know what the future holds.” It’s another to admit that you, yourself, don’t know today what you will even want in the future. And the truth is, few of us do. It’s hard to make enduring long-term decisions when your view of what you’ll want in the future is likely to shift.
	• Harvard psychologist Daniel Gilbert once said: At every stage of our lives we make decisions that will profoundly influence the lives of the people we’re going to become, and then when we become those people, we’re not always thrilled with the decisions we made.So young people pay good money to get tattoos removed that teenagers paid good money to get. Middle-aged people rushed to divorce people who young adults rushed to marry. Older adults work hard to lose what middle-aged adults worked hard to gain. On and on and on. “All of us,” he said, “are walking around with an illusion—an illusion that history, our personal history, has just come to an end, that we have just recently become the people that we were always meant to be and will be for the rest of our lives.” We tend to never learn this lesson.
	“Hold stocks for the long run,” you’ll hear. It’s good advice. But do you know how hard it is to maintain a long-term outlook when stocks are collapsing? Like everything else worthwhile, successful investing demands a price. But its currency is not dollars and cents. It’s volatility, fear, doubt, uncertainty, and regret—all of which are easy to overlook until you’re dealing with them in real time.
	• Thinking of market volatility as a fee rather than a fine is an important part of developing the kind of mindset that lets you stick around long enough for investing gains to work in your favor. Few investors have the disposition to say, “I’m actually fine if I lose 20% of my money.” This is doubly true for new investors who have never experienced a 20% decline.
	• Part of why bubbles are hard to learn from is that they are not like cancer, where a biopsy gives us a clear warning and diagnosis. They are closer to the rise and fall of a political party, where the outcome is known in hindsight but the cause and blame are never agreed upon.
	• Bubbles aren’t so much about valuations rising. That’s just a symptom of something else: time horizons shrinking as more short-term traders enter the playing field. It’s common to say the dot-com bubble was a time of irrational optimism about the future. But one of the most common headlines of that era was announcing record trading volume, which is what happens when investors are buying and selling in a single day. Investors— particularly the ones setting prices—were not thinking about the next 20 years. The average mutual fund had 120% annual turnover in 1999, meaning they were, at most, thinking about the next eight months. So were the individual investors who bought those mutual funds.
	• Data from Attom, a company that tracks real estate transactions, shows the number of houses in America that sold more than once in a 12-month period—they were flipped—rose fivefold during the bubble, from 20,000 in the first quarter of 2000 to over 100,000 in the first quarter of 2004. Flipping plunged after the bubble to less than 40,000 per quarter, where it’s roughly remained since.
	• The formation of bubbles isn’t so much about people irrationally participating in long-term investing. They’re about people somewhat rationally moving toward short-term trading to capture momentum that had been feeding on itself. What do you expect people to do when momentum creates a big short-term return potential? Sit and watch patiently? Never. That’s not how the world works. Profits will always be chased. And short-term traders operate in an area where the rules governing long-term investing—particularly around valuation—are ignored, because they’re irrelevant to the game being played.
	• When a commentator on CNBC says, “You should buy this stock,” keep in mind that they do not know who you are. Are you a teenager trading for fun? An elderly widow on a limited budget? A hedge fund manager trying to shore up your books before the quarter ends? Are we supposed to think those three people have the same priorities, and that whatever level a particular stock is trading at is right for all three of them? It’s crazy.
	• Pessimism just sounds smarter and more plausible than optimism. Tell someone that everything will be great and they’re likely to either shrug you off or offer a skeptical eye. Tell someone they’re in danger and you have their undivided attention.
	• If a smart person tells me they have a stock pick that’s going to rise 10-fold in the next year, I will immediately write them off as full of nonsense. If someone who’s full of nonsense tells me that a stock I own is about to collapse because it’s an accounting fraud, I will clear my calendar and listen to their every word.
	• But a few other things make financial pessimism easy, common, and more persuasive than optimism. One is that money is ubiquitous, so something bad happening tends to affect everyone and captures everyone’s attention.
	Another is that pessimists often extrapolate present trends without accounting for how markets adapt.
	Third is that progress happens too slowly to notice, but setbacks happen too quickly to ignore.
	• Growth is driven by compounding, which always takes time. Destruction is driven by single points of failure, which can happen in seconds, and loss of confidence, which can happen in an instant.
	• It’s easier to create a narrative around pessimism because the story pieces tend to be fresher and more recent. Optimistic narratives require looking at a long stretch of history and developments, which people tend to forget and take more effort to piece together.
	• Consider that 85% of active mutual funds underperformed their benchmark over the 10 years ending 2018. That figure has been fairly stable for generations. You would think an industry with such poor performance would be a niche service and have a hard time staying in business. But there’s almost five trillion dollars invested in these funds. Give someone the chance of investing alongside “the next Warren Buffett” and they’ll believe with such faith that millions of people will put their life savings behind
	• Half of all U.S. mutual fund portfolio managers do not invest a cent of their own money in their funds, according to Morningstar. This might seem atrocious, and surely the statistic uncovers some hypocrisy.
	• Charlie Munger once said “I did not intend to get rich. I just wanted to get independent.”
	• Every stock we own is a low-cost index fund. I don’t have anything against actively picking stocks, either on your own or through giving your money to an active fund manager. I think some people can outperform the market averages—it’s just very hard, and harder than most people think.
	• (The statistics show 85% of large-cap active managers didn’t beat the S&P 500 over the decade ending 2019.)
	• Sharp inequality became a force over the last 35 years, and it happened during a period where, culturally, Americans held onto two ideas rooted in the post-WW2 economy: That you should live a lifestyle similar to most other Americans, and that taking on debt to finance that lifestyle is acceptable.
	The lifestyles of a small portion of legitimately rich Americans inflated the aspirations of the majority of Americans, whose incomes weren’t rising.
	A culture of equality and togetherness that came out of the 1950s–1970s innocently morphs into a Keeping Up With The Joneses effect.
	During a time when median wages were flat, the median new American home grew 50% larger.
	The average new American home now has more bathrooms than occupants. Nearly half have four or more bedrooms, up from 18% in 1983.

[phreakv6]

Algorithms To Live By, Brian Christian & Tom Griffiths, 2016 - Enjoying a book this much should be a sin. I had a wide grin for the most part of this book as I could relate so much with the thought-process. I have been using lot of analogies in one of my lines of work to describe performance issues like latency, race conditions, space-time tradeoffs using analogies with bank tellers, cars, driving and train stations now for years because its easier for most people to understand. It has always been nice to bring computing problems to human scale and this book does the same in terms of applying learnings from computer science to life.

Here are the algorithms to live by, with my notes from each section (Warning: This is long. Seriously long)

1. Optimal Stopping - Evaluating choices - Stop at 37% (in no-information games)

• The crucial dilemma is not which option to pick but how many to even consider

• Ordinal numbers and cardinal numbers - Relative ranking between options vs ratings on a general scale

• Two ways of failing - stopping early and not discovering the best option or stopping late and passing by the best option

• “Look-then-leap” is precisely what it is - Look at 37% of the options (or 37% of total time available) to form an intuition and gain information and then leap.

• Variants - If there is 50/50 chance of proposal being accepted (option has agency), then stop at 25% and if immediate proposals are a sure thing but belated ones are 50/50, be noncommittal till 61%.

• If we know exactly what we are looking for - then its a full-information game - stop when you find the first option that matches

• Corollary - In the case of slim pickings, lower your standards and when there is more fish in the sea, raise them

• Turning no-information games into full-information ones - Finding where your option stands relative to the total population at large changes the look-then-leap to threshold rule (Higher odds of finding best option)

• Where to Park - Pass up all vacant spots available before a certain distance to the destination and then take the first one that’s available after - choose distance based on occupancy rate (Rational brain does this amazingly intuitively)

2. Explore/Exploit - Latest vs Greatest

• Life is a balance between novelty and tradition

• Explore vs Exploit depends on how much time you have in the game - In the game life, it depends on your age

• We are more likely to try a new restaurant when we move to a city than when we are leaving it

• Explore when you have the time to use the resulting knowledge, exploit when you are ready to cash in. The interval makes the strategy

• Movie sequels are “exploit” strategies. It is short-termist and maybe studios think they are in the end of the interval (their imminent demise)

• Win-stay, Lose-shift strategy (Multi-armed bandit problems) - Stay with a winning option long as it pays and shift when it doesn’t. Though Win-Stay is generally a very optimal strategy for most games, Lost-Shift may not be - It could be a rash move. Good options shouldn’t be penalized for being imperfect (Bit of Bayes will help?)

• Gittins index for multi-armed bandit problems (Devised for R&D in pharma for drug trials) - Uses geometric discounting. Play the arm with the highest index.

• An untested rookie is worth more (early in the season) than a veteran of seemingly equal ability, because we know less about him - Taking future into account drives us more towards novelty

• Regret and Optimism - To try and fail is at least to learn, to fail to try is to suffer the inestimable loss of what might have been (Chester Bernard)

• Regret will never stop increasing, even if you pick the best possible strategy - because even the best possible strategy isnt perfect every time. Only rate of growth of regret goes down over time with the best strategy

• Minimum possible regret is regret that increases at a logarithmic rate (As many mistakes in the first year as the next 9 in the decade which would be the same as what you would make in the next 90)

• Upper confidence bound algo (Optimism in the face of uncertainty) - Doesn’t care about past payoffs as much and looks for what could perform better in the future (restaurant with a single mediocre review has a higher potential for greatness than one with 100s of mediocre reviews)

• Assume the best about new people, things or options in the absence of evidence to the contrary - in the long run, optimism is the best prevention for regret

• Hippocratic oath in medicine - Do no harm (fundamental of medical ethics)

• Adaptive trials as an alternative to current clinical trials - chance of using a given treatment is increased with each win and decreased with loss (mod of Win-stay, lose-shift)

• In general people tend to over-explore (could be because the world is a restless bandit and things change all the time - that bad restaurant doesn’t have to remain bad - maybe its better now)

• Having instincts tuned by evolution for a world in constant flux isn’t necessarily helpful in an era of industrial standardization

• Childhood is designed in such a way that exploration can be done without concern of payoffs

• Our intuition about rationality are often informed by exploitation than exploration - if you treat every decision as your last - only exploitation makes sense

• Elderly have few social connections by choice focusing on meaningful connections (exploit)

3. Sorting
• The tabulation of the 1880 census took 8 years, barely finishing by the time the 1890 census (US) began

• First stored program ever written was for sorting (IBM)

• Finding largest, smallest, rarest, indexing, finding dupes - they all start with a sort

• Sorting has negative operating leverage (more to sort, worse the cost) Corollary: Do laundry more often if sorting socks is becoming a pain

• Worst case analysis lets us make guarantees on computing times - (Big-O notation in comp-sci always deals with worst case times - as size of problem increases, how does the running time change?)

O(1) = constant time - Computing time remains same irrespective of size
O(n) = linear time - Twice the guests in a dinner table, twice the dish takes to come around the dinner table
O(n^2) = quadratic time (If each guest hugged each other)
O(2^n) = exponential time - Where each guest doubles your work
O(n!) = factorial time - Like shuffling a deck and hoping it were sorted (Run through all combinations)

• Bubble sort - Sorting a book shelf pass after pass in quadratic time

• Insertion sort - Pull off all the books and put them back one at a time at the right place (Again quadratic time)

• Even checking if a bookshelf is sorted is in linear time involving a full scan of the shelf (So sorting in constant time O(1) is out of the question). Ideal solution lies between Linear and Quadratic times (Mergesort)

• Mergesort has a linearithmic time O(n log n) - Sorting two already sorted stacks is a lot easier than one big stack. Excellent for parallelizing - Call a bunch of your friends over and give them all a pile to sort and then merge them all in the end (Difference in times in staggering - like 29 passes vs a few million for census level items)

• Bucket sort - Sorting by categories - This can be done in almost linear time (Though will depend on number of categories so O(mxn). Libraries do this all the time by genre

• Sorting something you will never search is wasteful. Searching something unsorted is merely inefficient (Okay if you do it infrequently). Err on the side of messiness (I do, with my bookshelf which is merely bucketed into read and unread. Besides, I enjoy the searching :-))

• We search with our quick eyes and sort with our slow hands - important thing to consider as well. Sometimes mess is the optimal choice

• Round-robin and ladder tournaments have quadratic complexity and can be quickly overwhelming when number of teams increases

• Single-elimination tournament can only decide Gold but not silver or bronze accurately (Still we use it in Olympics and in smartphone camera shootouts)

• Games with noise like soccer (fluke or luck plays a part) gain from inefficiency of a Bubble sort. (IPL uses a comparison counting sort)

• One of the important skills as a poker player is to be able to evaluate how good you are

• Blood sort - Pecking Order/Dominance hierarchies - Establishing a pecking order avoids a lot of confrontation and bloodshed.

• Pecking order is easier to establish in a herd/flock/pack if group size is small. Ethical raising of livestock must take this into account (keep group size small)

• When every knows their position in a pecking order, no games ensue (be it poker cash games or fight among monkeys)

• Race is fundamentally different from a fight - Marathon is cardinal than ordinal - naturally orders the set by finish time and doesn’t need pairwise comparisons

• Things like national GDP establish a dominance hierarchy among nations and avoids conflicts to some extent

4. Caching

• What to do when cache gets full is decided by an eviction policy (or replacement policy). Idea is to minimize the number of times you can’t find what you are looking for in the cache

• The idea is to evict whichever item it is we will need the longest from now (almost like clairvoyance)

• Random eviction - As the name suggests - nuke whichever and make space, even if its your favorite shirt in the daily rack

• FIFO - First In, First Out - Get rid of whatever has been sitting on longest

• LRU - Least Recently Used (Gold standard) - Get rid of whichever has not been used recently. Considering frequency of use can also help improve along with recency

• Nearest thing to clairvoyance is to assume history repeats itself - backward

• People watch movies set close to where they live (So Netflix caches these movies in the closest CDN)

• Brain forgets to reduce cognitive load. Unlike eviction or replacement, brain loses references (Ebbighaus foregetting curve)

• Human society functions like human beings in forgetting (similar curve for newspaper headlines) - Availability bias is caused by this

• Cognitive decline from ageing could be caused due to sheer amount of information that must be processed

5. Scheduling - First things first

• Minimizing maximum lateness - Pick the task with the earliest Due date first (or serve customers who arrived first)

• Minimizing the number of foods that spoil in a fridge - Eat food by earliest expiry date but toss the largest item if it means consuming more items (Moore’s Algorithm)

• Minimizing length of TO DO list - start with the items with shortest processing time

• Only prioritize a task twice as long only if its twice as important (form some rules of thumb)

• A man with one watch knows what time it is, a man with two is never sure

• Give a system an overwhelming number of trivial things to do and the important things get lost (denial-of-service)

• Staying focused on getting the weighty important things done - can also be an non-optimal approach (Mars Pathfinder issue due to priority inversion)

• Precedence constraint (fancy name in scheduling theory for task dependency)

• Problems without an efficient solution (Intractable problems)

• Straightening out a to-do list can become an item on the to-do list when the system doing the scheduling is same as the one being scheduled

• Price paid for switching tasks - context switch (that’s why 16 hour days are more productive than 8 hour days sometimes in writing and programming)

• Everyone you interrupt more than a few times in an hour has a danger of not doing anything at all

• Thrashing - when all you do is context switch without doing anything productive

• When a juggler takes one more ball, he doesn’t lose just that ball, he loses all

• Interrupt coalescing - responsiveness (how quickly can you respond) and throughput (how much work can you get done) are always at odds - better to have someone answer the phone (responsive) while you get work done (throughput)

• Donald Knuth - patron saint of minimal context switching (mails replied once in 3 months)

6. Bayes Rule - Making decisions from small data

• (w+1)/(n+2) - Laplace’s law for estimating probabilities where w is wins and n is attempts (When you have one win from one attempt, you have 67% chance, which is reasonable “optimistic” estimate than over-confident 100%)

• It was Laplace who did all the heavy-lifting though its called Bayes rule

• How long will something last - As long as it has already lasted is a useful rule of thumb (Gott’s Copernican principle). This sounds very much like Lindy effect

• Copernican principle is just Bayes rule with an uninformative prior

• The richer the prior information we bring into Bayes rule, the better our predictions

• Be wary of what distributions your real world priors draw from (power-law vs gaussian). Populations and incomes follow power-law than normal

• Copernican principle is Bayes rule for priors that are power-law distributed. (Multiplicative based on power-law exponent - hence 2x for Lindy and 1.4x for movie collections based on collections so far)

• Things that are neither more nor less likely to end because they have gone on for awhile (Erlang distribution) - Predictions based on additive rule.

• Small data is big data in disguise - The reason why we are able to predict well from small data is because our priors are so rich

• Good prediction require good priors

• Our judgements betray our expectations and our expectations betray our experience

• ability to resist temptation maybe a matter of expectations than willpower (if you know how long you have to wait, you develop the will to wait)

• Priors are formed by experience but when a species gains language and the ability to speak, priors are formed not just by personal experience but by shared experience which may have a skew to special/interesting things affecting priors

• News reports interesting/special things which may be infrequent - don’t let infrequent things reported frequently affect your priors (protect your priors for they are what you base your decisions on)

7. Overfitting - When to think less

• How hard to think, how many factors to consider? (There’s wisdom in thinking less)

• Better fit doesn’t mean better prediction

• Overfitting taste - when food taste excellent but nutritionally poor (Taste was a fit for nutrition as required in the past)

• Company will build whatever it is the CEO decides to measure (Sam Altman)

• Ruthless and clever optimization of the wrong thing (Goodhart’s law, though the book doesn’t mention it by name)

• Training scars (A cop habitually handed the pistol to the assailant after grabbing it from him as he had done so hundreds of time in training)

• Cross-validation detects overfitting by seeing how well a class generalizes what it learnt (to see if it was only taught to the test)

• Regularization - placing constraints that penalize models for their complexity

• Lasso used frequently in ML drives a lot of weights down to zero

• Language forms a natural Lasso - Convey what you intend fast or you lose the audience’s attention

• Less information, computation and time can improve accuracy (Elevator pitches and investment thesis in few lines)

• Nudge a model towards simplicity by controlling how quickly it adapts to new data

• single most important factor than multi-factors lead to better predictions in some cases

• Early Stopping provides the foundation for a reasoned argument against reasoning (thinking person’s case against thought)

• If you have high uncertainty and limited data - Stop Early

• Further ahead you are in a brainstorming session, thinner the pen’s stroke size should be (simplification by stroke size - can’t get into minor details when coming up with broad outlines due to pen size)

• You can also regularize to the page (what doesn’t make the page isn’t important)

8. Relaxation

• Traveling salesman problem is O(n!) problem. Its not that a computer can’t find the shortest route but that as number of towns increase, the problem has n! solutions and finding the best out of it is computationally hard

• Defining difficulty - Any algo that runs in polynomial time O(n^2) or O(n^3) is considered efficient or in general O(n^m) even. O(n!) is considered intractable

• Relax the traveling salesman problem by allowing him to retract to the same town or visit same town multiple times and form - this shortest route produces the minimum spanning tree

• Constraint relaxation like above lets us solve an easier version of a complex problem making the intractable, tractable and making it a starting point

• If you are willing to accept compromises, even the hairiest problems can be tamed

• Lagrangian relaxation - “Do, it or else!” problems replied with “Do it or else what?” - coloring outside the lines at a cost to make the intractable tractable. (Converting impossibilities into penalties and teaching the art of bending/breaking the rules and living with the consequences)

9. Randomness

• Choosing the random option feels like a cop out but its far from it

• You need to know when to rely on chance, in what way and to what extent

• Complex quantities can be estimated by sampling (value of pi can be estimated by dropping a needle on paper)

• Test of first-rate intelligence is the ability to hold two conflicting thoughts and still be able to function (F. Scott Fitzgerald)

• Monte Carlo simulations - Replacing exhaustive probability calculations with sample simulations

• Sieve of Erastothenes - One of the first algorithms for finding prime numbers in ancient Greece

• It is much easier to multiply two primes than factor them back out (especially for very large ones) - forms the basis of cryptography

• Testing for prime - primality - Miller’s approach is better than sieve of Erastothenes but it involves probability than certainty

• Along with Time and Space tradeoff, in recent times, the third dimension of error probability is added (You can get an answer fast but there is small chance of error)

• Bloom filters works like Miller-Rabin test for primality (Used for detecting malicious sites)

• Greedy/myopic algo - One that takes the best thing available, every step of the way (in the context of Gradient Descent as in ML or Hill-Climbing as used in the book). To get from a local minima to a global minima, you have worsen your solution a bit

• Use a little bit of randomness everytime you make a decision (Metropolis algorithm)

• Simulated Annealing (heating and then slowly cooling) from metallurgy is used in ML for optimization

• Even if you are in the habit of acting on bad ideas, you should always act on the good ones (Hill Climbing algo)

• Your likelihood of following a bad idea should be inversely proportional to how bad the idea is

• Front-load randomness, rapidly cooling out of it, using lesser and lesser randomness as time goes by, lingering longest as you approach freezing (Temper yourself, literally)

10. Networking

• Circuit switching - constant bandwidth, always on - made sense for human communication. But having a dedicated connection to something that’s never talking but when it does wants an immediate line gave rise to packet switching (like postcards moving at the speed of light)

• Packet switching - reliability increases exponentially with network size unlike circuit switching where calls fail if any link gets disrupted

• Byzantine generals problem (confirmation of receipt of message requires another message causing endless recursion)

• 10% of peak hour upstream traffic is Netflix ACKs

• Exponential backoff algorithm - The algorithm of forgiveness. Ubiquitous for reconnecting - Max delay length is exponential (Its a random number of seconds delay under max though to attempt reconnect)

• We must replace three strikes and you are out (finite forgiveness against infractions) with finite patience and infinite mercy (Simply take longer intervals to try again but never give up)

• Congestion/Flow control - AIMD - Additive Increase/Multiplicate Decrease (Another fantastic algorithm) - TCP sawtooth pattern is caused by this. I think this is a fantastic algorithm for allocation to bets/trades - keep adding by 1 until trouble ensues but when it does, cut back by half

• Control without hierarchy - More ants leave the nest, the more successful the foraging but unsuccessful returnees result in diminishment

• Every employee tends to rise to his level of incompetence (Peter Principle) - Every employee gets promoted but stagnates in a position where he doesn’t do well. So over time an organization is filled with people doing their worst in the post they are in. (Demotions help)

• With poor feedback from the listener, the story falls apart

• Photons that miss the retina aren’t queued for later viewing - In real life, packet loss is total

• It used to be that people knocked on your door and went home if there was no answer, now they wait in queue (on Email)

• Circuit switching to packet switching has happened to society - Instead of dedicated lines, we send messages and instead of reject, we defer

• Tail drop (Can’t accept any more messages)

• Companies that advertise fast internet connections are actually advertising higher bandwidth than lower latency

11. Game Theory

• Algorithmic game theory - cross-pollination between game theory and computer science

• Successful investing is anticipating the anticipation of others (Keynes) or what Average opinion expects the average opinion to be

• Halting problem - when a machine or mind tries to simulate something as complex as itself, it finds its resources maxed out, by definition

• You really want to play only one level above the opponent - if not you are going to think they have information they don’t really possess

• Equilibrium - Content with my strategy given yours, and you are content with yours given mine

• Every two player game has at least one equilibrium (John Nash)

• Predictive abilities of Nash equilibria only matter if they can be found

• If your laptop can’t find it, neither can the market

• A low price of anarchy means that the system is about as good on its own than being carefully managed

• Tragedy of the commons - two player prisoner’s dilemma extended to many players - we can easily end up in a terrible equilibrium with a clean conscience

• If the rules of the game force bad strategies, we shouldn’t change the strategies, we should change the game (reverse game theory or mechanism design - what rules will give us behavior we want to see?)

• If a tree grows taller to get more sunlight and the rest of the trees do too, to the same level - the canopy finally gets the same as it did before - except now it supports the trunk at a higher cost (Dawkins)

• Morality is herd instinct in the individual (Nietzsche). Emotion is mechanism design in the species

• Sealed-bid first price auction, Dutch auction (Descending) and English auction (Ascending). In a Dutch auction, its the absence of bid that reveals information

• Information cascade (or infinite misinformation) - When players take others’ actions for beliefs and act accordingly and that reinforces someone else’s belief. Consensus unglues from reality (Happens all the time in the stock market)

• Be wary of cases where public information exceeds private information (to avoid being trapped in information cascades) and also be wary of situations where you know more about what people are doing than why they are doing it and hesitant to overrule your own doubts

• Vickrey auction (second-best bid) - winner pays second best bid - participants are incentivized to be honest

• Any game that requires strategically masking the truth can be transformed into one that requires nothing but simple honesty

• Hell is other people (Sartre) - (Not because of maliciousness but because of the way they affect our beliefs)

• Popularity is complicated, intractable, a recursion in a hall of mirrors, but beauty in the eye of the beholder, is not. Adopting a strategy that doesnt require anticipating, predicting other’s tactics is one way to cut the Gordian knot of recursion

• Seek out games where honesty is the dominant strategy. Then just be yourself

If you have made it this far, this book is for you. 11/10

[phreakv6]

Bad Blood, John Carreyrou, 2018 - This is a well-written book that reads like a thriller. There’s a lot of interviews and research done here which isn’t surprising since it was the author that exposed Theranos to uncover the fakery. I did find lot of embellishments in minor details though which I am not sure people reveal in interviews but it was OK as creative liberties in re-telling of tales is common and also since it made for an engaging read.

‘Fake-it-till-you-make-it’ is quite common in tech start-ups (fake the product or even the business model) but where it perhaps went awry for Theranos was the extent to which it took it (sunk costs) - only problem here was that real patients were harmed due to the fakery which may not happen in a normal tech start-up. What was also surprising was the composition of the board (Mattis, Schultz etc. from former sec of state to sec. of defense and several other high-profile members) and how Elizabeth managed to influence them to the extent some of them believed her more than their own family (Halo effect). Elizabeth probably wielded her own reality-distortion field.

It is amazing that Theranos was valued near $10 billion, had investors from Rupert Murdoch, Walmart’s Walton family, Cox family and several other high-profile VCs who were all deluded. Always be wary of individual aura and powerpoint presentations with deluded projections detached from reality. This was a book in which I didn’t highlight a single line - Usually means I had no takeaways and mostly treated it as entertainment. 8/10

[Ansh_Gupta]

The book is written by Ben Horowitz, co-founder of the famous tech-focused Venture Capital Fund, Andreessen Horowitz. This one is more of a “management book” rather than a “business book”, has lots of practical insights for CEOs regarding how to manage their companies etc.
One general takeaway from this book is that some things in life are hard by nature, don’t try to make them easy or find a shortcut. Would rate the book 8/10.
Summarizing it below:

• The hard thing about hard things is that there is no formula for dealing with them

• Met his best friend and wife totally by chance (had to perform a dare to a random kid, who became his best friend eventually and was setup on a blind date which almost got cancelled, with his wife)

• Learned the most important rule of raising money privately: Look for a market of one.
You only need one investor to say yes, so it’s best to ignore the other thirty who say “no”

• If you are going to eat shit, don’t nibble: When he was the CEO of Loudcloud and the company had just gone public (during dot com boom), he chose to simply re-state guidance from $75M to $55M to investors instead of hiding it from the investors and causing pain to the company later

• Good Leadership: When Loudcloud later became Opsware and the company was in a crisis again, he was totally honest about the tough situation with the employees and even offered to help them find jobs if they decided not to stick with the company.
Result: only 2 employees quit, rest 78 stayed

• When one of the most important (but arrogant) clients was having a fit, the CEO actually found out how to “wow” the client by solving their pain points (unrelated to the product he had to deliver)

• Inserted an agenda item of “What are we not doing” in his weekly meetings, so that all the time is not spent only on what the company was doing

• “If I’d learned anything, it was that conventional wisdom had nothing to do with the truth and the efficient market hypothesis was deceptive…market were just very efficient at converging on a conclusion-often the wrong conclusion”

• “I learned one important lesson: Startup CEOs should not play the odds. When you are building a company, you must believe there is an answer and you cannot pay attention to your odds of finding it. You just have to find it. It matters not whether your chances are 9 in 10 or 1 in 1000; your task is the same”

• People often ask me, “What is the secret to being a successful CEO?”
Sadly, there is no secret, but if there is one skill that stsands out, it’s the ability to focus and make the best move when there are no good moves. It’s the moments where you feel most like hiding or dying that you can make the biggest difference as a CEO

• I follow the first principle of the Bushido- the way of the warrior: keep death in mind at all times.

• The positivity delusion: CEOs should tell it like it is because they are the ones who take bad news the hardest, others in the company can easily brush it off. If the company lost a big client, it’s important the whole organization understood why, so they can work on it together.

• If you run a company, you will experience overwhelming psychological pressure to be overly positive. Stand up to the pressure, face your fear and tell it like it is

• (The book also has a lot of interesting chapters like “How to fire an employee”, “How to fire an executive”, “How to demote a loyal friend”)

• One would think that after the dot-com crash of April 2000, companies like Cisco, Siebel and HP would realize that they would soon face a slowdown as many of their customers hit the wall. But despite perhaps the most massive and public early warning system ever, each CEO reiterated strong guidance.

When Ben asked Andy Grove regarding this, he replied that these great CEOs were not lying to investors, they were lying to themselves.

He explained that humans, particularly those who build things, only listen to leading indicators of good news. If a CEO hears that their product is growing at 25%, they will hire more people and if the product slows by 25%, they’ll just shrug it off.

• Nobody cares- All the mental energy you use to elaborate your misery would be far better used trying to find the one seemingly impossible way out of your current mess. Spend zero time on what you could have done, and devote all of your time on what you might do. Because in the end, nobody cares; just run your company.

• Take care of the people, the products and the profits- in that order.
Taking care of the people is the most difficult of the three and if you don’t do it, the other two won’t matter

• People at McDonald’s get trained for their positions, but people with far more complicated jobs don’t. It makes no sense. A lot of companies think their employees are so smart that they require no training, that’s silly.

• Training is quite simply one of the highest leverage activities a manager can perform. Let’s see the numbers:
If a manager puts on a series of 4 lectures, assuming 3 hours prep time for each one-hour lecture.
Say, you have 10 people in your department. Next year, they will work ~20,000 hours for the company and even if the training increases improvement by 1%, that’s a gain of 200 hours from an effort of 12 hours.

• Every really good, really experienced CEO shares one important characteristic: They tend to opt for the hard answer to organizational issues. If faced with giving everyone the same bonus to make things easy or with sharply rewarding performance and ruffling many feathers, they’ll ruffle the feathers.
Simply because they’ve paid the price for ‘management debt’ (which basically means doing something good in short-term which is bad in long-term)

• Sometimes an organization doesn’t need a solution; it just needs clarity. Once I made it clear that cursing was okay-so long as it wasn’t used to intimidate or harass-nobody had a problem with it anymore

• On employee titles: Marc Andreessen vs Mark Zuckerberg
While the former believes that out of all the things an employee asks for, title is the cheapest (be it VP, SVP etc.) but Mark Zuckerberg believes the opposite: Facebook actually has employee titles which are lower than industry standards and people joining Facebook have to take a title haircut. He believes this is important so that new employees don’t get better titles compared to existing better performing employees and boosts morale. FB misses out on a few people who don’t join the company for this reason, but they’re precisely the people who won’t be a good cultural fit for the company.

• Phil Jackson, the coach who has won the most NBA championships, was once asked about his famously flaky superstar Dennis Rodman, “Since Dennis Rodman is allowed to miss practice, does this mean other start players like Michael Jordan and Scottie Pippen can miss practice, too?” He replied, “Of course not, there is only room for one Dennis Rodman on this team…otherwise we would degenerate into anarchy.”

• Outside hire vs internal promotion: Depends on the particular skill you value for the role
For example, in an engineering position, the knowledge of the systems and code is highly valued and internal promotions tend to perform better but for a sales role, the opposite is true since knowing how other customers think is far more valuable than knowing about your own company and product

• Creating a company culture:

1. Desks made out of doors: Jeff Bezos incorporated frugality in Amazon’s culture from the very start, all desks that employees use would be built by buying cheap doors from Home Depot and nailing legs to them. This complements Amazon’s goal of delivering best value to the customer at a cheap price
2. Ten dollars per minute: When a16z was started, the founders knew that a lot of VCs made entrepreneurs wait for long periods of time in the lobby before a meeting. So, they set a rule that if any employee of 16z was late to the meeting, they’d pay $10 by the minute, to respect entrepreneurs time
3. Move fast and break things: Mark Zuckerberg deployed this motto at the start of Facebook, be innovative rather than being right every time
   Prior to figuring out the exact form of your company’s culture, be sure that the mechanism agrees with your values. For example, Jack Dorsey (when he was the CEO of Square) would never have desks made out of wood because at Square, beautiful design trumps frugality.

• Why dogs at work and yoga aren’t culture: It will not help establish a core value that drives the business and helps promote it in perpetuity. It is not specific with respect to what your business aims to achieve, yoga is a perk.
Perks are good, but they are not culture.

• Over the years, I’ve spoken to hundreds of CEOs, all with the same experience. It’s like the fight club of management: The first rule of the CEO psychological meltdown is don’t talk about the psychological meltdown.

• Tip to aspiring entrepreneurs: If you don’t like choosing between horrible and cataclysmic, don’t become CEO

• Focus on the road, not the wall: When someone learns to drive a race car, one of the first lessons taught is that when you are going around a curve at 200mph, do not focus on the wall; focus on the road. If you focus on the wall, you will drive right into it. If you focus on the road, you will follow the road. Running a company is like that.

• Whenever I meet a successful CEO, I ask them how they did it. Mediocre CEOs point to their brilliant strategic movies or clever business sense while great CEOs tend to be consistent with their answers, “I didn’t quit”

• When my partners and I meet with entrepreneurs, the two key characteristics that we look for are brilliance and courage. In my experience as CEO, I found that the most important decisions tested my courage far more than my intelligence.

• Every time you make the hard, correct decision you become a bit more courageous and every time you make the easy, wrong decision you become a bit more cowardly. If you are a CEO, these choices will lead to a courageous or cowardly company.

• Over the past ten years, technological advances have dramatically lowered the financial bar for starting a new company, but the courage bar for building a great company remains as high as it has ever been

• What makes people want to follow a leader?

1. The ability to articulate the vision (The Steve Jobs Attribute)
   Jobs’ greatest achievement as a visionary leader was in getting so many super-talented people to continue following him at NeXT and in getting the employees of Apple to buy into his vision when the company was weeks away from bankruptcy

2. The right kind of ambition (The Bill Campbell Attribute)
   Truly great leaders create an environment where the employees feel that the CEO cares more about the employees than she cares about herself. A huge part of why Bill has been so strong in this dimension is because he’s completely authentic. He would happily sacrifice his own economics, fame and glory for his employees.

3. The ability to achieve the vision (The Andy Grove Attribute)
   Last characteristic simply is competence. Andy Grove is remarked with transitioning Intel from a memory business to the microprocessor business and in making that change, he walked away from nearly all his revenue.

• Peacetime CEO vs. Wartime CEO
When Steve Jobs returned to Apple, the company was weeks away from bankruptcy and he needed everyone to move with precision and follow his exact plan; there was no room for individual creativity outside the core mission.
In stark contrast, as Google achieved dominance in the search market, Google’s management fostered peacetime innovation by encouraging employees to spend 20% of their time on their own new projects.

• Most people actually assume the opposite-CEOs are born, not made.
In athletics, some things, like becoming a sprinter can be learned relatively quickly because they start with a natural motion and refine it. Others, like boxing take much longer to master because they require lots of unnatural motions and lots of specific technique.
Learning to make this unnatural motion feel natural takes a great deal of practice. If you do what feels most natural as a CEO, you may also get knocked cold.

• At the time of any given decision, the CEO will generally have less than 10% of the information typically present in the post hoc Harvard Business School case study. As a result, the CEO must have the courage to bet the company on a direction even though she does not know if the direction is right.

• Of course, even with all the advice and hindsight in the world, hard things will continue to be hard things. So, in closing, I just say peace to all those engaged in the struggle to fulfill their dreams.

[phreakv6]

The Order of Time, Carlo Rovelli, 2017 - This is the closest living theoretical physicist to Feynman at present, in terms of the ability to explain insanely complex subjects to idiots like me. In this book he dissects time like a physicist poet and the takeaways were astounding for me. My perspective of time is completely changed from an absolute Newtonian perspective (time flows orderly from past, present to the future and the clock ticks the time away) to a relative one where time is a measure of change and is only present where there is change.

Since reading Proust’s In Search of Lost Time (Only Vol 1: Swann’s Way) and Thomas Mann’s Magic Mountain - both phenomenal explorations of time, I have often wondered about the passage of time, how the first day of a vacation in a new place feels like 2 or 3 days instead of 1 for eg. and the consequent possible subjectivity of time.

Here is my understanding of the book as notes (as well as some lines I liked)

• We inhabit time as fish live in water (familiar, intimate, ever-present)

• Do we exist in time or does time exist in us?

• Time passes faster in the mountains than at sea level (Gravity affects time) and is observable/verifiable with precision clocks (Einstein understood/predicted this before precise clocks could verify it)

• The ability to understand something before its observed is at the heart of scientific thinking (As in Einstein above)

• How does sun and earth attract each other without touching? Its because a mass slows down time around itself and as we get away from the mass, time passes faster (hence faster in the mountains) and movement of things is naturally inclined towards where time passes slower and these things only “appear” to fall in our perspective. In space where time is uniform, things do not fall

• Time passes more slowly for our feet than it does for our head!

• If different clocks mark different time, then which of them is “True time”? Neither. It is like dollars and pounds which have value relative to each other but no “absolute” value

• Heat is what makes time irreversible delineating past and future. A ball may continue bouncing forever if only there was no friction. Thoughts as well unfold from past to future because the brain produces heat in thinking. Heat is inextricably linked to the irreversible arrow of time

• Entropy - the measure of disorder and Clausius equation of change in entropy (S-S0) being equivalent to sum total (integral) of heat lost (dQ) from the system at temperature T (dQ/T) is the only equation in fundamental physics that knows the difference between past and the future

• Why does entropy increase? Or conversely, why in the past was entropy lower? Heat, entropy and lower entropy are notions that belong to an approximate statistical description of nature. If you could take into account all the possible states, and observe the microscopic state of things, time vanishes. The difference between past and future arises only from our own blurred vision of the world (Our inability to apprehend the world’s microscopic states)

• Fantastic thought experiment with cards - If you observe that a pack of cards is ordered such that first 26 are red and next 26 are black and shuffle them, the pack is now in disorder and entropy has increased. Same happens if the pack was ordered say numerically or had all hearts and spades as the first 26 and was shuffled. Things “appear” to be in disorder when we observe it in a “particular configuration”. An already shuffled pack is also in a “particular configuration” that is no different from a first 26 red and next 26 black configuration - hence the pack is merely taking one of the several equiprobable combinations on shuffling but it is our perspective that makes it feel like disorder is increasing - or disorder arises from observation of particular configurations

• Entropy as Boltzmann understood was the number of microscopic states our blurred vision failed to distinguish

• Time is also slowed down by speed like it is slowed down by mass. For everything that moves, time passes slowly. So not only is there a single time for different places, there isn’t even a single time for the same place

• Notion of “present” refers only to what’s closer to us. Present as we observe from a distant galaxy is what transpired in the past. Essentially there is no “Now” that applies to the entire universe (It is an illegitimate extrapolation of our experience)

• Temporal structure of spacetime is made up of light-cones (Explained nicely with genealogy). There is no before and after between any two elements while a before and after may exist between certain elements.

• How did we as humans get the idea that time passes at the same speed everywhere? For centuries we only had “days” as a measure of time, then the day was split into 12 hours (summer and winter hours were of different length consequently). First clocks were built in the 14th century and each had its own local time based on the sun. In the 19th century after telegraph and trains is when synchronization of clocks was done (along with timezones). Einstein worked in the patent office specifically on patents related to synchronizing of clocks realized it was an insoluble one. The synchronizing of clocks and Newtonian view of time passing uniformly is what skewed our perspective.

• Aristotle was the first one who understood that time was a measure of change. He believed that if nothing changes, time ceases to pass and in fact there is no time.

• Our intuitions aren’t natural and maybe influenced (The way we perceive Newtonian uniform time almost intuitively wasn’t how humans thought for millennia)

• What is there, where there is nothing? Newton believed space devoid of things was still space (more abstract in thought) while Aristotle believed there can be no space which has nothing. Einstein unified both approaches

• Granularity - A minimum scale exists for all phenomena. Nothing is valid everywhere. Also time isn’t continuous, it jumps discrete values and below this minimum interval, time does not exist

• We cannot think of physical world as made of things and entities - it is made of events and processes (Latter deals with change while the former with stasis)

• We do not have grammar adapted to say events are “has been” in relation to me but “is” in relation to you (This is seriously profound).

• Between energy and time is a close bond - a conjugate - like that between position and momentum or orientation and angular momentum

• Entropy of the universe was low in the past and always increases not because the universe was in a particular configuration in the past but it us that observed it which was in a particular configuration (As in the cards example earlier)

• Indexicality - words such as “You”, “I”, “now”, “this’, 'tonight” that take different meanings based on who says it under what circumstance

• It is entropy and not energy that drives the world - in a log of wood, or photons from the sun, there is low entropy

• Life reduces entropy around it but it does so by consuming things with low entropy (net-net its a self-structured disordering where overall disorder increases with respect to us - but is no different from rest of the universe)

• We have shaped the idea of human being based on our interaction with others (the first image most of us have of ourselves is the image we see as others see us - mostly our mothers)

• We are the reflection of the idea of ourselves that we receive back from our kind

• To understand ourselves we need to reflect on time but to understand time we need to reflect on ourselves

• We perceive time though we are in the present and our presence is instantaneous - because we retain a state of the past and we anticipate the future (like how a LSTM perceives time)

• We long for timelessness, we endure the passing of time: we suffer time. Time is suffering

• Yaksa asks Yudhisthira in the Mahabharata what is the greatest of all mysteries to which he replies - "Everyday countless people die and yet those who remain live as if they were immortals’

This book sent me on deeper introspection on the nature of us human beings which is rare for a serious work of science. Some of the meandering rivers of thought I have had since reading Proust’s ‘In search of lost time’ and Mann’s Magic Mountain appear to have found their ocean in this book. Very highly recommended. 11/10

[Malhar_Manek]

Hello everyone. I was reading Spy The Lie and as per some suggestions, was practising by looking at old interviews of fraudsters and trying to identify clues. On page 60, the writers say that refusal or reluctance to answer can be a red flag(if part of a cluster). I wanted to know, would you’ll consider Nirav Modi’s ‘no comments’ answer(India's most wanted man Nirav Modi - accused of £1.5bn fraud - living openly in London - YouTube) as refusal to answer and a red flag? Also, are there any other deceptive behaviours you could identify in this video?https://www.youtube.com/watch?v=jkZJyjLCbtE

[lingalarahul7]

A Piece Of The Action.

Notes:

APieceOfTheAction.pdf (133.1 KB)

Review:

This a super-niche book with a lot of details on America’s financial revolution history from the 1950s to 1990s.

If you are curious about below questions, go for the book. But would caution that the book has a lot of details which I felt are not necessary.

1. How were credit cards born? How did they work when there were no POS terminals? What were the initial challenges when banks were building credit card businesses? Who are ideal credit card customers for banks? How is interchange fee charged by the banks to merchants?
2. How was Visa formed and what does it do? How did it upgrade its systems over time?
3. How did mutual fund companies grab asset share from bank deposits towards money market funds during 1970s inflation? How did mutual funds attract public into investing into equity funds? How did money market funds respond when there were lots of defaults during early 1990s?
4. Who was America’s best mutual fund manager and what is his life story?
5. How did the middle class of America take October 13th of 1987, Black Monday? How was this stock market crash different from previous stock market crashes?
6. How did discount brokerage business evolve in the US? Why did Schwab stand-out among other discount brokerages in the country?
7. What problems did middle class America face during the 1970s inflation? What are good asset classes to invest during inflationary periods? How did US banking regulations designed during 1930s depression affect their macros during 1970s inflation?

[lingalarahul7]

Economic Survey 2020-21 Volume 1.

https://www.indiabudget.gov.in/economicsurvey/

Notes:

EconomicSurvey2020-21Volume1.pdf (129.2 KB)

Review:

Summary of India’s economic status.

Topics include

1. Reforms announced during the COVID-19 crisis.
2. Real impact of increasing debt, given high growth rates of the country.
3. India’s counter-cyclical fiscal policy
4. Government’s opinion on India’s Sovereign Credit Rating
5. Growth vs Inequality vs Poverty
6. Impact of healthcare spends on economy
7. Drifting India’s regulatory landscape to broad-level regulations from case-wise regulations
8. Impact of Forbearance introduced by RBI during GFC on India’s banks
9. Asset Quality Review report of Indian banks
10. Impact of PM-JAY on Indian poor households’ health

The report is highly biased in favor of the government. Statistics and data used in the report are smartly chosen to support arguments in favor of the government. Felt this a lot in topics where the book argues why India’s sovereign credit rating should be better than what it is currently and also in the Regulatory forbearance chapter where the Government blames RBI for the poor asset quality of India’s public sector banks.

Doesn’t yet give a full picture of the Indian economy. I guess one needs to read the Volume 2 too.

[phreakv6]

Euclid’s Window, Leonard Mlodinow, 2001 - What a perfect companion to ‘The Order of Time’ which talks more about time while this book is more about space. Though written 16 years apart, somehow subconsciously I had chosen this right around the same time to read. This book gives a brief history of how humanity has perceived space around it and how it has evolved along with the ability of brain to think in abstractions and do science and math, from Aristotle watching masts of ships disappearing in the distance and presuming earth to be curved 24 centuries back to the latest string theory (as of 2001).

Here’s a summary of the chronology of our perceptions, along with the proponents in that timeline (and some other stuff I thought were interesting)

• Geometry literally means “earth measurement” - ancient Egyptians and Babylonians (~2000 BC) used it to measure volume of earth dug out (Harappans probably got it through the Indus-Mesopotamian trade and culture exchange)

• The Egyptian govt. had land taxes calculated based on the height of the year’s flood on the Nile and the surface area of land holdings (~2000 BC)

• Egyptians approximated the area of a circle to be that of a square made with 8/9ths of the circle’s diameter (Gives a pi value of 3.16 which isn’t bad for an approximation)

• "Hypotenuse in Greek means “stretched against”. The word came much later but around 2580 BC Egyptians used ropes with knots in them to measure vertices of triangles with 3 slaves (pyramids probably used the same concept)

• Mesopotamian civilization flourished between 2000-1700 BC with its ruler Hammurabi (~1800BC). They could calculate manpower required to dig a canal based on the shape, volume and rate of earth removal. They even calculated compound interest

• Babylonians probably knew Pythagoras theorem even before the Greeks. They had recorded triplets like 3,4,5 and even big ones like 3456,3367 and 4825 - odds of coming up with these randomly is very slim

• Thales of Miletus, Wealthy merchant from ~620 BC - Laid out the foundations of modern reasoning and abstract thought. Considered the world’s first scientist/mathematician. He predicted the solar eclipse of 585 BC after traveling to Babylon and learning the science and math of astronomy (Probably the connecting factor between Egypt/Babylon and Greece in progress)

• Thales systematized geometric theorems

• Anaximander, student of Thales, 550BC created the first map of the world

• Pythagoras of Samos rose around the time Thales was a frail old man. He visited Miletus and met Thales

• Greeks abstracted away the mathematics of the Egyptians - A line was a tugged rope, rectangle the boundary of a plot of land, space was mud, soil and air etc.

• A line can be edge of a pyramid, boundary of a field or the path the crow flies - knowledge about one transfers to the other due to the abstraction

• Pythagoras discovered “square numbers” (4,9,16) and “triangular numbers” (3,6,10) playing with pebbles to make squared and triangles

• Distinction between mathematics and science didn’t become clear until the 19th century

• Pythagoras at 50, returned from Miletus and formed a religion and sought followers (Much of stories attributed to Christ were probably originated by Pythagoras in the 5th century BC). This may also be the first “cult” in known history

• Pythagoreans proposed earth was a sphere

• Pythagoras’ teachings were lost when Telys attacked Croton and most of Pythagoras’ followers were killed and his teachings survived by word of mouth until they were revived by the Romans in 300 BC.

• Euclid (~300BC) opened the school in Alexandria. Wrote “Elements” which encapsulated most of the knowledge in Geometry (originated from Babylon, abstracted by Pythagoras and other Greeks) with its 23 definitions,5 postulates, 5 common notions and 465 theorems with proof

• 2D space with no reference to real-world was first conceptualized by Euclid

• Archimedes (~250BC) came up with the latitude and longitude

• Library of Alexandria held around 200k-500k papyrus scrolls

• In 212 BC Eratosthenes (chief librarian) measured the circumference of the Earth using length of sun’s shadows (there’s nice video of Carl Sagan explaining how it works)

• Aristarchus (~200 BC) measured size of the moon and distance from earth (again Alexandrian)

• Archimedes (~200 BC), another Alexandrian discovered the now famous lever and buoyancy.

• Hipparchus (200BC) yet another Alexandrian observed heavens for 35 years and worked out a model of the Solar system and could predict lunar eclipses accurate to the hour

• Claudius Ptolemy (2nd century AD), again an Alexandrian wrote Geographia and initiated Cartography (map-making) - was a standard reference for 100s of years

• By 2nd Century BC math, physics, cartography, engineering had all made great strides. We knew matter was made of atoms, invested logic and proof, geometry and trigonometry and even a rudimentary form of calculus. If this civilization had flourished, we could have sent men to the moon by the 10th Century

• Hypatia, 370 AD was the last great scholar of Alexandria. She wrote significant commentaries on Diophantus’ Arithmetica and Apollonius’ Conic Sections (still famous works)

• In 391 AD, a Christian mob attacked and burned the library of Alexandria. Hypatia was killed by Christian monks in 415 on the morning Lent and her limbs torn apart and scattered around the city. With that came the Dark Ages when religion and scriptures took over and the Church and supported by the Church, the idea that earth was flat again began to gain ground, along with violence, plague and pestilence

• Abelard, Aquinas, Bacon and Occam made some progress in the middle ages but were excommunicated or killed (only Aquinas was smooth enough to survive). Civilization flourished in the east in the Dark ages, making progress in mathematics (Brahmagupta with zero in 6th century AD, Hindu-Arabian numerals, Algebra in Persia etc)

• Oresme, 14th Century AD, influenced by Aristotle’s works into French. He invented the Graph. He discovered how trend worked against time. He had discovered that area under the curve for uniform velocity or constant acceleration (rectangle and triangle respectively) gave the distance.

• Oresme also realized you can’t talk of motion without a frame of reference (you are moving or at rest, depending on it) - he essentially discovered Galilean relativity before Galileo.

• Oresme also pondered if it was earth that moved around the sun but gave up on it for belief in scriptures and fear of the church (he died a Bishop)

• Rene Descartes, 1596 - invented the Cartesian co-ordinates and converted geometry to algebra - another level of abstraction. In 1637, published Discourse, a work of Philosophy, science and math

• Newton brought heaven and earth together in the 17th century when he applied his classical mechanics to bodies on earth as well as the heavens

• The parallel postulate is what lead to the discovery of curved space

• Gauss by 1824 had worked out non-Euclidean geometry for curved spaces (hyperbolic geometry).

• In Gauss’s day, science and philosophy were one. Physics was “natural philosophy”

• Hyperbolic geometry - Sum of angles in a triangle could be less than 180 deg. No similar triangles exist and for any line, given a point, there could be many parallel lines passing through that point and not just one as according to Euclidean geometry.

• Poincare-line is the shortest-path between two points on a surface (geodesic)

• Elliptic space - No parallel lines can exist. All lines invariably intersect

• When Gauss undertook geodesic survey to measure distance between cities that he encountered the random errors will be distributed in a bell-shaped curve around a mean

• Differential geometry - Analyzed using differential calculus using coordinate method invented by Descartes

• Larger triangles formed on the earth’s surface deviate larger from Pythagoras’ theorem of Euclidean spaces (Haversine or Great circle distance or Poincare line vs Euclidean distance)

• Reimann’s, (19th century) work on differential geometry was the cornerstone for Einstein’s general theory relativity. In a Reimann spherical universe of 40 miles, on a clear day, you could see the back of your own head. With it came the demise of in-between, behind, front, inside and outside which now became contradictions

• Hilbert, 1899 came up with clear foundations for Euclidean geometry stating the assumptions into explicit statements and thereby coming up with Axioms

• James Clerk Maxwell, 1865 discovered the electromagnetic field (later interpreted and simplified by Lorentz)

• Bertrand Russell, 1903 in ‘Principles of Mathematics’ - All mathematics should be derivable from logic.

• Kurt Gödel, 1931 - In a system of sufficient complexity, there must exist a statement that cannot be proved to be either True or False. In essence there must exist some truth which cannot be proved, given what we know (Incompleteness theorems) which flew in the face of Russell and Whitehead’s insistence on proof and derivations from logic when it was impossible to do so.

• Maxwell’s electromagnetic theory needed waves and waves needed a medium and so the belief on “Ether” came about

• Lorentz was the leading theoretical physicist of the 1890s, surmised the existence of local and universal time and also that mass of electron must be affected as it passes through ether. Poincare questioned if speed of light could be the limit for the universe and also subjectivity of space and time concluding there can be no absolute time - These laid the groundwork for Einstein.

• Einstein was always interested in Kantian perspective that time and space are products of our perception (Interestingly Gauss dismisses Kant’s Critique of Pure Reason after reading it 5 times)

• Einstein’s work in 1905 working as a patent clerk was the most productive by any scientist (six published papers) since Newton in 1665-66 at his mother’s farm

• Einstein - Objects do not have length in an absolute sense. Their length depends on the observer who is looking

• Worldline - Time coordinates that vary but space coordinates that do not

• “If a person falls freely he will not feel his own weight” - Einstein called this the happiest thought of his life

• Newton himself was unhappy with the instantaneous transmission of force (gravitation for eg.) - Einstein understood this to be the work of curved space around the object that we perceive as gravity - Gravity is not a force but a property of space

• Schrodinger and Heisenberg around 1925 independently discovered ways to replace Newton’s laws to be in sync with quantum principles (wave mechanics and matrix mechanics) - Paul Dirac proved both were equivalent and unified it as Quantum Mechanics

• Witten, 1995 - Space and Time do not actually exist - they are approximations of something more complex - a case of mathematical abstractions being ahead of physics - won him the fields medal in math than a Nobel in Physics

• Feynman thought string theory was nuts

• If you formally extend Einstein’s field equations to 5 dimensions, you get maxwell’s equations (If you are climbing a 3D mountain in 2D space, you will feel a repulsion not unlike a magnetic field) - Kaluza’s point was that gravity and magnetism are components of the same thing

The book ends with a sort of a primer on string theory which flew a bit above my head as I could not understand it intuitively. I took exhaustive notes on what seems to be the history of math/science pertaining to space because it is fascinating the way things have evolved and the many dead-ends we have taken and the many theories which were ahead of their time and the many which were kept out due to our religious biases (Humanity achieved almost nothing of value in Science and Math between 5th and 15 century). Seeing the evolution and mapping it in my head was a very rewarding exercise for me. 11/10

[edwardlobo]

Just because it’s called Pythagoras theorem it doesn’t mean Pythagoras discovered it. A simple google search on who discovered Pythagoras theorem will show it was discovered atleast 1000 years before Pythagoras

Names are used for some things by popularity.
For instance if you say someone was born 100 year bc, doesn’t mean you believe in Jesus just because you used a reference

While I agree one needs to remain knowledgeable on ones own heritage and it also encourages patriotism, that shouldn’t be the main focus of our learnings.

In ancient times, the North part of India probably would have considered themselves more closer to Central Asia than to south India!

What matters is the progress done now, new discoveries and educating our children to be on the forefront on new studies irrespective of where the history of those studies came from.

[phreakv6]

Hi @vh1 -

If you see the book’s premise, it is that though Euclid or Pythagoras get the credit, there is a lot that has happened prior that has driven that and throughout the book there are lot of people who have stumbled onto something but someone else has got the credit.

For eg.

1. Bolyai and Lobachevsky came up with hyperbolic geometry and were peers to Gauss (the term non-Euclidian though was coined by Gauss) and Riemann is the one credited with a lot of the work
2. Schrodinger and Heisenberg both discovered Uncertainty principle but it is named Heisenberg’s uncertainty principle as we know it
3. Fermat also invented Cartesian coordinates at the same time as Descartes - But it is Descartes who gets the credit. Descartes had the bad habit of not including citations and Fermat had the bad habit of not even publishing
4. Some of the work solidified by Einstein’s general theory of relativity was worked on by Lorentz and Poincare

and so on. It is pretty common in science and mathematics that multiple people stumble onto something at around the same time because they are swimming the same ingredient soup.

Now coming to specific case of ignoring Indian mathematicians. I have done some basic work on it.

Baudhayana - Going by the time range of 8th century BC - Babylon had Pythagorean triplets in 1700 BC though there isn’t sufficient documentation on how they arrived at it. For eg.3456,3367 and 4825 was found on a Babylonian tablet from 1700 BC. So this is about 1000 years before Baudhayana. It is a working theory that Babylon and Harappans had trade and culture links and it is possible that we acquired that knowledge through that.

Aryabhatta - He lived in the 6th century AD and his notable achievements include prediction of eclipse, rotation of earth on its axis, calculation of value of pi and other geometric calculations relating to earth. Most of these appear to be predated by Thales, Archimedes and possibly even prior (pi value was estimated by Egyptians ~2000 BC). There are some achievements like sinusoidal functions, quadratic equation and algebra which do sound modern but I haven’t verified if there is a prior.

Bhaskara 1, 629 AD - Of the notable works, include his approximation for sin x. There are some others like his 1+(p-1)! being divisible by p if p is a prime which are disputed. The Hindu Decimal system with zero at its start and also representation of 20,30 etc. using zeros is without a doubt our biggest contribution (Though it gets referred to as Hindu-Arabic number system). This probably leap-frogged number theory in a way Greek numerals could not have. This gets lot of credit from the west as well - You can see in this thread as well that I mentioned it in the summary of “Against the Gods”

Bhaskara 2, 12th century AD - Again during the middle ages when the west was regressing, we were making great progress (As the book’s author also acknowledges) in algebra, number theory, calculus and trigonometry.

Ramanujan - His work is probably the most groundbreaking of all names you have mentioned because he was way, way above the rest and his notebooks are still revered and he rightfully gets a lot of respect. The man who knew infinity is fantastic book that introduced me to Ramanujan (Again written by a Western author Robert Kanigel). I do still wonder though if his being Indian had anything to do with his discoveries though we do like to celebrate that association (perhaps its ok to do). I would think he was ignored along with a lot of celebrated mathematicians in this book (no Euler, no Cardano, no von Neumann either) because this was a book about “Space” and in that there wasn’t any contribution from Ramanujan in that aspect.

I thought it would help us all if we put out what we did or didn’t do, rather than making generic statements that we should study our own. It might also help if we saw ourselves as human-beings who borrow from each other and make our species progress in our understanding of life rather than by arbitrary boundaries of nations.

[edwardlobo]

@phreakv6

Ramanujan - His work is probably the most groundbreaking of all names you have mentioned because he was way, way above the rest and his notebooks are still revered and he rightfully gets a lot of respect. The man who knew infinity is fantastic book that introduced me to Ramanujan

What I found intriguing was that Ramanujan himself said his “ works” were shown to him in a dream by the goddess he worshiped. I think he was born in a wrong time with a wrong skin colour

[Chins]

I’d also like to build on @phreakv6’s post by talking about attribution and recognition.

There are some brilliant mathematicians and physicists that are being recognised from India, except that it’s difficult for people outside the circle of academia to see this recognition that happens almost on a daily basis. For example, Abhay Ashtekar is someone who played (plays) an instrumental role in developing one of the candidate theories for quantum gravity. You wouldn’t have heard of him by popular accounts, but he has around 9000 citations and has written one of the most famous papers in modern physics. There’s also Ashoke Sen, who has inspired over 10,000 works of literature.

There are thousands of scientists that have played a role in modern mathematics and physics, but we seem to only want to remember those that lived during the ancient times. The other problem that was pointed out earlier is that there was almost no communication between the scientific circles back then, so it was almost impossible to attribute novel findings globally.

@edwardlobo

What I found intriguing was that Ramanujan himself said his “ works” were shown to him in a dream by the goddess he worshiped. I think he was born in a wrong time with a wrong skin colour

As much as I admire him, the problem with this is that science is a method; a means to an end, not the end in itself. What matters most is the precise statements one makes in their logic, not the end result of a theorem. This was the main contention that Hardy had with Ramanujan, and the topic of proofs is well documented in his life story.

Ultimately, the goal of these books is to give you a window into a subject and start a journey of interest.

@phreakv6

It might also help if we saw ourselves as human-beings who borrow from each other and make our species progress in our understanding of life rather than by arbitrary boundaries of nations.

This is a really nice way of looking at it; that the knowledge doesn’t belong to Einstein, or Ramanujan or Maldacena, but to us all. Feynman said this beautifully in his Nobel winning speech: Imagination reaches out repeatedly trying to achieve some higher level of understanding, until suddenly I find myself momentarily alone before one new corner of nature’s pattern of beauty and true majesty revealed. That was my reward.

The last thing I’d say is that the way we can do this is by encouraging our children to take up science and literature should this take up their interest, and not drive them away towards traditionally safe fields of study.

[vh1]

@phreakv6

It is pretty common in science and mathematics that multiple people stumble onto something at around the same time because they are swimming the same ingredient soup.

Here we are talking about a timeline of thousand years before Pythagoras. Yet to find any mention of him anywhere in any of the western chronicles! (A footnote would suffice, thank you).

Very good to see a brief about some of the ancient Indian mathematicians. Hope it raises curiosity among us who may be interested in this and want to explore further.

Two pointers for further understanding for curious souls.

Indian_Mathematicians_and__Their_Contributions_ijariie2761.pdf

Dr. M.D Srinivas talks about how evolution of Mathematics in India is different from Mathematics in Europe. He traces the history of Indian mathematics for last two thousand years and shows that how it evolves independently of European Mathematics.

Evolution of Indian Mathematics

@phreakv6

It might also help if we saw ourselves as human-beings who borrow from each other and make our species progress in our understanding of life rather than by arbitrary boundaries of nations.

While one agrees with the idea of borrowing from each other, national boundaries are harsh reality of this world and till such time they exist one will remain an Indian trying to understand more about India/Indians also!

Thanks.

[Malhar_Manek]

All I Want To Know Is Where I’m Going To Die So I’ll Never Go There

Few key takeaways from the book:

• It is far easier to consistently avoid doing dumb things than to consistently do smart things

• ‘Invert, always invert’ : Before understanding what to do, it is important to understand what not to do. This reminds me of a story of Tenali Rama where he goes to buy vegetables, and pretends that he doesn’t have much money, so he gives the vendor a bag and asks the vendor to put all the rotten, stinking vegetables in that bag. Then, he asks the vendor to keep that bag aside; he then removes another bag and asks the vendor to give him the most fresh vegetables from the ones that are remaining!

• The power of incentives: ‘if you want ants, put sugar on the floor’. Stock options, warrants etc. are in fact incentivizing bad behaviour. The story of FedEx night shift employees was quite interesting.

• Do what you love: do a job that you would do even if you weren’t paid for it; but at the same time- be a realist, and make sure your passion is aligned with your talent

• Don’t bother about insignificant mistakes: this reminded me of Rakesh Ji’s quote “Never be afraid to make a mistake. Only make one you can afford, so you may live to make another one”

• Saving the best for the last, my favourite part was about the business model of Reed-Elsevier scientific journals; just incredible! What an incredible money minting machine!
  

  

Overall, the book was good, but not great, in my opinion: as I already knew many of the concepts like circle of competence, too tough, moats etc., but it was certainly an entertaining read. Overall, I think anyone who has read a lot about Sir Buffett and Sir Munger will not derive much incremental value from this book, but it is surely worth keeping on the bookshelf!

8/10

*Also found this article on Reed-Elsevier’s remarkably profitable business model for anyone who’s interested: https://www.theguardian.com/science/2017/jun/27/profitable-business-scientific-publishing-bad-for-science

[Malhar_Manek]

This book is essentially a compilation of Amazon letters to shareholders, as well as Sir Jeff Bezos's interviews- in other words, a distillation of Sir Bezos's wisdom

Few key takeaways from the book:

• Focus on the long term: giving up long term opportunities for short term gain is seldom a good idea
• Emphasize on growing free cash flow per share in the long term, rather than trying to maximize quarterly EBITDA numbers
• Big wins compensate for many mistakes: as Sir Mark Cuban says- "you only have to be right once". A few big wins at Amazon, like Amazon Web Services and Kindle, have compensated for Fire Phone, Destinations, Amazon Auction and many more
• Obsess over customers instead of competitors: over the long term, what is good for customers is inevitably good for shareholders
• Innovate and don't be afraid to fail: 'failure and innovation are inseparable twins'
• Quick decision making: make decisions with 70% of the information; don't wait till 90%
• Disagree and commit: often, you will have scenarios where you disagree with a colleague's ideas; in such cases, don't spend much time debating and arguing. Instead, use the phrase 'disagree and commit'
• Find the root cause of problems and eliminate problems from the base
• Regret minimization: try to project yourself to age 80, and determine whether or not you would regret making a particular decision. This simplifies the decision-making process
• Growth ≠ Value Creation: contrary to popular belief, earnings growth is not directly equal to value creation. Growth is merely an amplifier; true value creation occurs when the capital investment required for growth is lesser than the discounted value of future cash flows derived from the investment. In the absence of this criteria being fulfilled, growth actually destroys value*

Overall, the book was amazing! Definitely among the best books I have ever read. Must read!

10/10

*In one Motilal Oswal Wealth Creation Study, Sir Raamdeo Agrawal makes a similar point: https://www.youtube.com/watch?v=v69D_pV17_A&t=2146s