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@0xmarginman omg ) this is my article,thanks
WESTERN UNIVERSITIES CHARGE $8,000 FOR THIS ONE CLASS. THIS INDIAN PROFESSOR GAVE IT AWAY FOR FREE. IS ELITE TUITION A SCAM?
Watch this lecture. Prof. S. Lakshmi Bala from IIT Madras walks through a complete masterclass on a plain blackboard.
Zero paywalls. No sign-up required. Just raw, unedited graduate lectures.
Here is the economic reality. Western universities rely on artificial scarcity. They package standard curriculum behind $2,000-per-credit paywalls and call it elite.
In the digital age, the marginal cost of distributing knowledge is zero. Programs like NPTEL proved that educational gatekeeping is dead.
Colleges no longer hold a monopoly on world-class information. They only hold a monopoly on the expensive piece of paper at the end.
The smartest engineers in tech are already building off free archives like this.
Would you spend $50,000 on a university degree when the exact same material is free online? Drop your take below.
CASINOS PAY QUANTS $800K A YEAR TO STOP THIS EXACT EXPLOIT. WAS THIS GENIUS ARBITRAGE OR CHEATING?
Don Johnson took Atlantic City for $15 million. He never counted a single card.
No sleight of hand. No illegal tech. Just raw negotiation.
He convinced desperate casinos to give him a 20% loss rebate alongside modified table rules.
Here is the deep mathematical exploit.
A 20% rebate acts like a free put option on your capital. It creates extreme payoff asymmetry. Your downside stops at 80 cents on the dollar, but your upside stays at 100%.
When you reset your playing blocks at specific profit targets, the house edge instantly flips into a positive expected value (+EV) trade.
He didnβt beat the dealer. He executed financial risk arbitrage against a casino's balance sheet.
Amateurs try to play a bad hand masterfully. Pros redefine the contract terms before ever sitting down.
If a casino willingly signs a mathematically flawed deal, is it fair to ban the winner? Drop your take below.
@0xmarginman Definitely saving this video, they explain things so interestingly
THE MOST-WATCHED EDUCATIONAL YOUTUBE CHANNEL ON EARTH ISN'T RUN BY A FAMOUS PROFESSOR OR A SILICON VALLEY STARTUP. IT'S A GOVERNMENT PROGRAM MOST PEOPLE OUTSIDE INDIA HAVE NEVER HEARD OF.
It's called NPTEL β a joint initiative between India's IITs and IISc, the country's top engineering and science schools. Right now it hosts over 3,200 full university courses, taught by the same professors who teach paying students on campus, filmed lecture-hall style and uploaded with zero login wall and zero tuition.
I checked the actual numbers instead of taking the claim at face value. NPTEL's YouTube channel has crossed 1.86 billion views and 5.6 million subscribers β making it, by raw numbers, the most-watched educational channel on YouTube, ahead of any Western university's public course library. It's been running continuously since 2003, longer than most MOOC platforms have existed at all.
No production budget, no animated graphics, no algorithm-optimized thumbnails. Just professors teaching the exact same material they teach paying students on campus, uploaded for free.
One example among thousands: Dr. S. Lakshmi Bala's Quantum Mechanics I runs through the exact syllabus a physics graduate student pays tuition to sit through β postulates of quantum mechanics, angular momentum, quantum optics β filmed with a blackboard and a static camera, nothing else.
Western universities charge thousands of dollars per credit hour for exactly this material. India recorded the entire thing and put it online for anyone with an internet connection.
The real question isn't whether this archive exists. It's why almost nobody outside India has ever heard of the biggest free education library on the planet.
CARD COUNTING IS 100% LEGAL. CASINOS BAN YOU FOR IT ANYWAY, BECAUSE THE HOUSE EDGE ONLY EXISTS AS LONG AS NOBODY'S ACTUALLY TRACKING THE ODDS.
Mike Aponte was a big player and manager on the MIT Blackjack Team, part of a group of students who turned card counting into a science and quietly walked away with millions from the MGM Grand, The Venetian, The Mirage, Treasure Island, and the Bellagio through the 1990s. His biggest single win: roughly $500,000 in one weekend, Super Bowl weekend 1995. His biggest single loss: $130,000. Card counting isn't cheating, isn't hacking the machine, isn't marking cards β it's tracking which high and low cards have already been played and betting bigger when the odds tilt in your favor. Purely mental math, 100% legal, and casinos hate it anyway, because the house edge only works if the odds never actually shift against them.
The team's real skill wasn't the counting itself. It was the acting β playing perfect strategy while looking exactly like every other tourist losing money at the table, staying one step ahead of pit bosses whose entire job was catching exactly this. Eventually the casinos did catch up, banning key players and forcing new disguises and rotations.
Their story became the basis for the book "Bringing Down the House" and the movie "21." Aponte later became the first-ever World Series of Blackjack champion, walking away with $100,000 in prize money β and today he teaches the exact math he once used to beat Vegas, as a consultant and keynote speaker.
The house always wins on average. Aponte's entire career was proving "on average" has exceptions, if you actually do the math nobody else bothers to run.
@0xmarginman Inkredible ππ±
THIS 7-MINUTE SENATE CROSS-EXAMINATION OF BILL GATES TEACHES MORE ABOUT DEFLECTION THAN ANY HARVARD CASE STUDY.
One question. Asked four different ways. Watch how Gates stalls before admitting the restriction.
"Well, partly you're using legal terms I'm not familiar with."
"I don't think these are legal terms, Mr. Gates."
Netscape's CEO sat right in the room. AOL bought his company later that year.
Here is the masterclass in corporate defense. Never give a direct 'yes' or 'no.' Gates reframes the premise. He feigns ignorance on basic words. He forces the senator to define terms instead of arguing facts. Itβs a classic deposition tactic. Shift the focus to vocabulary, and you control the clock.
Media trainers charge $10,000 a day for this pivot. Gates pulled it off under federal oath.
https://t.co/hGCpanmclq
SHIA LABEOUF PREPARED FOR A MOVIE ROLE, ACCIDENTALLY TURNED $20,000 INTO NEARLY $489,000, AND WATCHED HIS TRADING MENTORS GET ARRESTED.
While getting into character for Wall Street: Money Never Sleeps, Shia LaBeouf went completely down the trading rabbit hole. In just a matter of months, he flipped a $20k bankroll into almost half a million dollars, passed the licensed broker exam, and took a seat on an actual trading desk.
"Before anything even got started β before I even met director Oliver Stone β I walked into a Schwab office in Encino and said, 'Look, Iβm getting ready for a role.' One guy recognizes me and goes, 'Oh man, youβre the kid from that movie with Megan Fox!' He got super excited and gave me a full behind-the-scenes crash course on how everything works."
"Once I got to New York and met a crew of high-level guys, I figured if I was ever going to put actual money into the market, now was the time. So I dropped 20 grand in. Before I knew it, that 20 grand snowballed into $489,000. I was staring at almost half a million bucks in my portfolio."
"The wildest part? The firm actually handed me a $1 million desk account to trade live firm capital during prep because my character was a prop trader. Out of the nine guys who trained me back then, four of them were later arrested and are currently serving time in prison for insider trading."
https://t.co/hGCpanmclq
EVERYONE QUOTES "NEVER LOSE MONEY, NEVER FORGET RULE NUMBER ONE." ALMOST NOBODY HAS ACTUALLY SAT THROUGH THE HOUR WHERE WARREN BUFFETT EXPLAINS WHAT IT MEANS.
October 1998. University of Florida. A room full of MBA students, no slides, no prepared remarks β just Buffett taking questions for an hour, free, unscripted. Investors are still pulling lessons out of that recording twenty-seven years later.
He'd spent the month before quietly trying to help bail out Long-Term Capital Management, a hedge fund staffed with Nobel laureates that had just collapsed using leverage and models Buffett never fully trusted in the first place. Their math was elegant. Their math also assumed markets would keep behaving the way history said they should, right up until the moment they didn't. Buffett walks into the room carrying that lesson fresh, and it shapes almost everything he says next.
He opens with the line he's repeated for decades: "Rule number one, never lose money. Rule number two, never forget rule number one." Most people who quote it stop right there and miss the actual point. He wasn't claiming he'd never taken a loss β he has, plenty of times, and says so in the same talk. He was describing a filter for what you're even allowed to bet on in the first place: only businesses you understand well enough to be genuinely confident about, nothing else, no matter how exciting or complicated the story sounds. Complexity, in his framing, isn't sophistication. It's usually just risk you haven't found yet.
Then he walks through See's Candies as the working example β Berkshire bought it in 1972 for $25 million, a business selling roughly 16 million pounds of candy a year at under $2 a pound. Nothing complicated about it. Understandable margins, predictable demand, no exotic assumptions required to know what you were buying. He contrasts it, gently, with the kind of instrument LTCM was running β beautiful on paper, unknowable in practice.
Financial advisors build entire careers charging asset-under-management fees for decades to deliver some slower, more expensive version of "stay inside your circle of competence." Buffett handed the whole framework away in one unscripted Q&A, to a room of students who almost certainly had no idea they were sitting in on one of the most replayed hours in the history of investing.
It's still free, still online, still exactly as unpolished as it was that afternoon in Florida. Most people who've watched it can still recite both rules word for word and still couldn't tell you, if you pushed them, why either one actually changes how they invest.
https://t.co/hGCpanmclq
THE NIGHT JAMIE DIMON GOT FIRED FROM CITIGROUP, FIFTY SENIOR EXECUTIVES SHOWED UP AT HIS APARTMENT. HE CALLED IT "BEING AT MY OWN WAKE."
He'd spent 15 years building the company alongside his mentor, Sandy Weill. In 1998, Weill called him in, listed a few org changes, then told Dimon to resign. Dimon said okay β he already knew it was arranged, the board had voted, the press release was written. He went home to his wife and three daughters. The youngest, ten, asked if they'd have to sleep on the streets.
Two years later he became CEO of Bank One, a Chicago bank that had just posted a $511 million loss. Three years after that: a record $3.5 billion profit. JPMorgan Chase bought Bank One in 2004. By 2005, Dimon ran the combined bank β now the largest in the country, built partly from the wreckage of the company that fired him.
He called Weill a year after the firing. Told him directly he thought Weill had gotten it wrong for Citigroup. Then admitted his own mistakes. Weill acknowledged both.
Dimon has talked since about what he actually looks for hiring senior people now: "Would you have your child work for that person? Half the time we promote people, we would not let our kid work for them."
Getting fired didn't break the career. It became the rΓ©sumΓ©.
https://t.co/hGCpanmclq
"YOU TAKE PEOPLE OUT TO DINNER AND YOU SAY, ORDER ANYTHING YOU WANT."
Milton Friedman's setup for the single clearest explanation of government waste ever recorded, and it takes under two minutes.
There are exactly four ways to spend money, he said, and only one of them is actually efficient.
Spend your own money on yourself β you're careful about both the cost and the quality, because both come out of your own pocket. Spend your own money on someone else β you still watch the cost, but you care less about the quality, because you're not the one using it. Spend someone else's money on yourself β you stop caring about cost, since it's not your money, but you care a lot about quality, because you're the one who benefits.
Then the fourth box, the one that explains almost every dollar a government spends: someone else's money, on someone else. Nobody in the transaction has any reason to watch the cost or the quality. The person paying isn't the one deciding. The person deciding isn't the one paying. The person receiving isn't paying for it either.
Friedman's point wasn't that government workers are careless people. It's that the incentive structure itself guarantees waste, independent of anyone's character β the same person who negotiates hard for their own dinner reservation will approve a bloated budget line without blinking, because the accountability loop that makes them careful in box one simply doesn't exist in box four.
Four boxes, ninety seconds, and it explains more about budget waste than most economics textbooks manage in a chapter.
https://t.co/hGCpanmclq
BERNIE MADOFF RAN A $65 BILLION FRAUD FOR 20 YEARS. ONE AFTERNOON WITH A SINGLE FORMULA WOULD HAVE CAUGHT HIM.
That single check β a digit count, not an audit β would have caught Bernie Madoff's $65 billion fraud in an afternoon, twenty years before anyone bothered to run it.
In 1938, physicist Frank Benford discovered that across river lengths, street addresses, stock prices, and population data, the leading digit 1 shows up nearly three times more often than intuition suggests it should. The exact rule: P(d) = log10(1 + 1/d). It gives 1 a 30.1% share, 9 barely 4.6%, and the curve holds no matter the currency or unit involved.
The reason it exposes fraud: people who invent numbers spread the digits out to look random β too many 5s, 6s, and 7s, not nearly enough 1s. Real data is never that democratic. It clusters on small leading digits, consistently, everywhere.
Auditors have relied on this for decades. The IRS uses it to flag suspicious tax returns. Researchers ran it against Enron's reported figures and against Greece's national accounts before its debt crisis β both failed the test. So did Madoff's returns, the single time anyone checked.
Twenty years, $65 billion, and the tell was sitting in his own filings the entire time β not hidden, just never counted.
https://t.co/hGCpanmclq
"DO YOU THINK I WOULD HAVE GONE DOWN THERE AND SPENT MY MONEY FOR EIGHT YEARS, KNOWING I WAS TRESPASSING?"
That's Denise Ezell. She won $127,000 fair and square. The casino decided, after the fact, that it didn't have to pay β and that's the exact risk sitting inside every financial contract with a counterparty who gets to decide whether to honor it.
She'd gambled weekly at MGM Grand Detroit for eight years, no issues, no warnings, no letters. A welcomed regular the entire time. On October 30, 2023, on what she called her last bet of the night, a side bet on progressive blackjack dealt her a four-card straight flush. The dealer erupted. The whole table congratulated her. She'd already started thinking about what the money would fix.
Then a pit boss pulled her aside and asked for her ID β routine, she assumed. Minutes later, casino staff told her she couldn't have the money. She'd technically been trespassing the entire time, tied to a 2015 argument with her cousin that a security guard once called "panhandling." She says she was never formally notified of any ban after that night, and kept gambling there weekly for eight more years without a single issue.
This is counterparty risk in its purest form. Being right about the bet was never the actual risk. The real risk was always whether the party on the other side would pay once the number came in β and that party controlled the decision the entire time, unilaterally, after the fact, using a reason it had never bothered to mention until the one night it was expensive to ignore.
It's the same mechanism that nearly took down the global financial system in 2008. AIG had sold enormous volumes of credit default swaps, priced correctly or not, and when the bill came due, the payout depended entirely on AIG's ability and willingness to make good on the contract β not on whether the underlying bet was sound. The math held. The counterparty almost didn't.
Ezell spent months trying to resolve it directly with MGM and the Michigan Gaming Control Board before filing a federal lawsuit in June 2024, seeking the $127,000 jackpot plus $75,000 in damages.
A correct bet and a paid bet are two different things. The gap between them is always the counterparty β and you rarely find out how wide that gap is until the exact moment you need it to be narrow.
https://t.co/hGCpanmclq
ISAAC NEWTON, THE SMARTEST MAN IN ENGLAND, USED TO SEND PEOPLE WITH HARD MATH QUESTIONS TO SOMEONE ELSE.
"HE KNOWS THESE THINGS BETTER THAN I DO."
Every insurance company on earth still prices risk using a curve first sold for one shilling in a London coffee house by that same man.
His name was Abraham de Moivre. France stripped its Protestants of their rights in 1685, and de Moivre, a Huguenot, was jailed for his religion before escaping to London. No English university would hire a foreign refugee, so he worked the only market that would take him: gamblers at Slaughter's Coffee House, paying a shilling each for their exact odds.
The gamblers wanted a single number. De Moivre was quietly building the machine behind it. In 1733, in a seven-page Latin pamphlet passed privately between friends, he found a way to approximate the binomial distribution for large numbers β and showed it settles into a smooth, bell-shaped curve. It was the first appearance of the normal distribution, seventy years before anyone else fully understood what it was.
That curve now sits under every actuarial table, every political poll, every risk model on Wall Street. His 1725 book on life annuities became the foundation the insurance industry still stands on. The curve itself got named after somebody else.
He died in 1754, half blind and poor, in the city that never gave him a university post. Late in life he noticed he was sleeping fifteen minutes longer each night, summed the pattern, and calculated the exact day the total would reach twenty-four hours. He died on that day.
The house always wins because a broke refugee wrote down, precisely, by how much.
https://t.co/hGCpanmclq
"Mechanism envy" β falling in love with a tool before you've asked what problem you're actually solving. A dead MIT professor coined it, and Wall Street has never stopped doing it.
Quant firms pay half a million dollars for something this same professor taught for free, fifty years running.
Patrick Winston ran the MIT AI Lab for twenty-five years. He watched generation after generation of engineers fall for the same trap β neural nets, genetic algorithms, Bayesian methods, a new tool every few years, always the same blind spot underneath.
His fix, taught for half a century: start with the competence you're trying to understand. Find a representation that exposes the real constraints. Only then reach for a method. Skip that order, and you're guessing with expensive machinery.
Wall Street has the identical disease, just with better marketing. A trader buys a Bloomberg terminal before learning expected value. A founder hires a data team before understanding base rates. A retail investor opens a brokerage app before finding out the number on the fund brochure isn't the number that actually hits their account.
What quant firms are really paying for isn't the method. It's five representations: expected value, base rates, ergodicity, conditional probability, signal versus noise. Five ways of seeing that reshape a bet before anyone touches a model.
Winston died in 2019. The lecture is still free. The five representations fit in a single article, and almost nobody installs them before reaching for the tools.
The representations cost nothing. Installing them first is the entire edge.
https://t.co/hGCpanmclq
You were about to spend an hour on Netflix tonight. The man who could've taught you more in that same hour died three months ago.
His name was Joel Peterson. He spent 33 years teaching at Stanford's Graduate School of Business, chaired JetBlue Airways for 12 years, ran Trammell Crow when it was the largest private real estate development firm on earth, and personally backed or launched over 250 companies β Bonobos, Trunk Club, Asurion, Vivint among them.
In 2007, he gave a lecture called "How to Negotiate and Get What You Want." No tricks, no manipulation, just principles built from decades of actual deals. His core idea cuts against almost everything negotiation content on the internet teaches: solve for fairness, not for winning. He said it built longer relationships than any clever tactic ever did.
He died November 25, 2025, at 78, after complications from a stroke. Condoleezza Rice, his colleague at Stanford, called him "a rare combination of kindness and principle." Students flocked to his classes for three decades because his skills in the classroom were, in his colleagues' words, legendary. He won the school's top teaching awards twice, a decade apart.
The lecture is still free, still online, still an hour long. Most people watching it tonight will spend less time on it than they spend on a single episode of whatever they were about to stream instead.
Skip the show. He spent 33 years making sure this hour was worth more.
https://t.co/hGCpanmclq
You've probably read "Zero to One." You've probably never seen where it actually came from.
Spring 2012. Peter Thiel β PayPal co-founder, first outside check into Facebook β taught one class at Stanford called CS183: Startup. A student, Blake Masters, posted his lecture notes online for free after every single class. No book deal yet. No agent. Just notes, typed fast enough to keep up with a billionaire thinking out loud.
Those notes got read by more people than the lecture hall could ever hold. Two years later, the material became "Zero to One" β now recommended reading in nearly every startup accelerator on earth.
One line from the original lecture explains why: "A business creates X dollars of value and captures Y percent of it. X and Y are independent variables." Founders obsess over X β market size, the slide that makes a pitch deck look massive β and skip the harder question entirely: even if you create all this value, how much of it do you actually get to keep? Plenty of huge, world-changing companies made their founders nothing, because Y was close to zero the whole time.
The eBay case study in that same lecture wasn't the eBay you know today. It opened with Pez dispensers and Beanie Babies β a tiny, almost embarrassing market β before Pierre Omidyar's platform expanded into what it became.
The notes are still free. Most people quoting the book in their own pitch deck have never actually run their business through the X and Y question.
https://t.co/hGCpanmclq
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