On the Edge

1. The "River" and "Village": Two Tribes Clashing Over Risk and Values.

Maybe Netflix Guy and Strip Club Guy aren’t even shopping at the same grocery store anymore; Netflix Guy moved to the country now that he doesn’t need to be in the office, and Strip Club Guy moved to Miami—and was probably playing against me in the poker tournament.

Two distinct tribes. The author identifies two major cultural groups in modern American life: the "River," composed of skilled gamblers, tech entrepreneurs, investors, and quants, and the "Village," encompassing those in government, media, and traditional academia. These tribes have fundamentally different approaches to risk, rationality, and social norms, leading to increasing conflict and bifurcation in society.

Clash of values. Riverians prioritize analytical thinking, decoupling ideas from context, independent-mindedness, and risk tolerance. They often view the Village as overly political, conformist, paternalistic, and risk-averse. Conversely, Villagers are skeptical of unregulated capitalism, concerned about moral hazard, and see Riverians as naive about politics and sometimes morally suspect.

Growing divide. The COVID-19 pandemic highlighted these differing risk preferences, making them public and influencing everything from where people live to how they vote. This cultural clash is escalating into open conflict, with powerful figures from both sides vying for influence and control over key institutions and narratives.

2. Expected Value and Game Theory: The Foundational Language of the River.

If a model says that Trump’s chances are 29 percent and the market price is 17 percent, the correct play is to bet on Trump—big.

Quantifying uncertainty. The core concept uniting the River is Expected Value (EV), the average outcome over the long run. Riverians apply this probabilistic thinking to gambling, investing, and life decisions, seeking opportunities where the potential payoff outweighs the risk, even if the outcome is uncertain.

Strategic interaction. Game theory, pioneered by John von Neumann, studies strategic behavior where players' actions impact one another. Key concepts include:

• Nash Equilibrium: A state where no player can improve their outcome by unilaterally changing their strategy.
• Prisoner's Dilemma: A scenario where individual rational choices lead to a collectively suboptimal outcome, highlighting the difficulty of cooperation.
• Mixed Strategy: Randomizing between options when multiple choices have the same EV, often used for deception.

Beyond zero-sum. While game theory originated in zero-sum games like poker, it applies broadly to situations involving cooperation, competition, and coordination, from nuclear deterrence to market pricing. Understanding game theory is crucial for navigating complex interactions in the River and beyond.

3. Poker: The Archetypal River Game, Transformed by AI and Human Psychology.

If you took an amateur from today, and you put him back fifteen, twenty years, he would probably crush those games.

Evolution of skill. Poker, particularly no-limit Texas Hold'em, has evolved from a game of intuition and rudimentary odds calculation to a highly sophisticated, data-driven discipline. The "Poker Boom" and the advent of computer "solvers" have revolutionized strategy, making the game significantly tougher for human players.

Man vs. Machine. Solvers calculate Game Theory Optimal (GTO) strategies, which are defensive and unexploitable. While computers excel at GTO play and complex calculations, human players still rely on:

• Intuition and pattern recognition (System 1 thinking)
• Reading opponents for "tells" (physical or verbal cues)
• Adapting exploitative strategies to counter opponents' specific weaknesses

Psychology under pressure. High-stakes poker is a whole-body experience, triggering physiological responses like increased heart rate. Managing anxiety and avoiding "tilt" (suboptimal play due to emotional distress) is crucial. Players like Phil Hellmuth and Maria Ho excel at reading opponents and leveraging psychological edges, demonstrating that poker remains a "people game" despite algorithmic advancements.

4. Risk-Taking: A Whole-Body Experience Beyond Rational Calculation.

But fundamentally, gambling for large amounts of money—enough money that you do brush up against your pain threshold—is a whole-body experience.

Physiology of risk. Risk-taking isn't purely cognitive; it triggers physiological responses. Neuroscientist John Coates's research shows that hormones like testosterone and cortisol influence traders' behavior, sometimes leading to irrational exuberance or excessive risk-aversion.

Intuition and stress. The body registers risk before conscious awareness. This intuitive response, honed by experience, can be a valuable guide, as seen in the Iowa Gambling Task. However, intense pressure can also lead to anxiety spirals or "tilt," hindering rational thought.

Experience matters. Repeated exposure to high-stakes situations helps individuals manage stress and channel physiological responses productively. This is evident in:

• Elite athletes performing under pressure
• Military personnel in combat
• Experienced poker players making critical decisions

While some risk-taking may seem irrational, the ability to manage the physical and emotional aspects of risk is a key differentiator for successful individuals in the River.

5. Habits of Successful Risk-Takers: Courage, Adaptability, and Strategic Empathy.

You have to recognize that you have agency and authorship and sometimes bold action is the best course of action, even if the conditions and the outcome [are] uncertain.

Beyond the numbers. Successful risk-takers, whether quants or those facing physical danger, share common traits:

• Cool under pressure: Executing calmly when others panic.
• Courage: Willingness to take calculated chances and embrace competition.
• Strategic empathy: Understanding opponents' perspectives to anticipate their actions.

Process over results. They focus on making the right decision based on available information and probabilities, rather than dwelling on outcomes influenced by luck. This mindset is crucial for navigating high-variance environments.

Adaptability and agency. Successful risk-takers are often generalists, comfortable with uncertainty and able to adapt to new situations. They understand their own agency and are willing to take bold action, knowing when to "raise or fold" rather than passively calling.

6. The Casino Business: An Algorithmic Engine Optimizing for Consumption.

Understanding why somebody would engage in an activity where they know in advance—absolute certainty, undoubtedly, far more probable [than not] that you’re going to lose your money…and yet do it willingly and do it over and over and over again—[that] always surprised me.

Evolution of Vegas. Las Vegas transformed from a frontier gambling town to a highly regulated, corporate-owned entertainment hub. Developers like Steve Wynn pioneered the mega-resort model, where non-gaming revenues (hotels, restaurants, shows) became increasingly important.

Algorithmic optimization. Modern casinos, influenced by data-driven approaches, use sophisticated analytics to maximize profits. Key strategies include:

• Increasing the "hold percentage" on slot machines, knowing players can't detect the difference.
• Designing games and environments to reduce friction and encourage continuous play.
• Using loyalty programs to track customer behavior and incentivize spending.

Exploiting human psychology. While some gamblers seek action and excitement, many slot players seek escape, entering a "machine zone" to avoid real-world pressures. Casinos cater to this by providing immersive, rewarding experiences that smooth the ride down to zero, sometimes leading to addiction.

7. Sports Betting: A High-Stakes Game of Skill, Information, and Constant Competition.

“A bottom-up guy, no matter how good his model is, no matter how smart he is, if he can’t bet, he’s worthless,” said Gadoon Kyrollos. “Me? All I know how to do is bet.”

Skill vs. hustle. Sports betting is a complex game requiring both analytical skill (building models, handicapping) and betting knowledge (understanding markets, getting money down). The most successful bettors, like Billy Walters and Rufus Peabody, combine these approaches.

The market is efficient. Betting lines are set by market-makers who incorporate information from sharp bettors. This creates a highly competitive environment where edges are thin, often requiring bettors to win just over 52.4% of bets to break even due to the "vig" (house cut).

Getting money down. Even with a winning model, the biggest challenge is often getting sportsbooks to accept large bets. Retail books limit winning players, forcing sharps to:

• Find market inefficiencies quickly ("steam chasing")
• Use "beards" (others who place bets on their behalf)
• Constantly seek new opportunities as old ones disappear

The industry is an algorithmic arms race, with both books and bettors using data and tactics to gain an advantage, making it a microcosm of modern capitalism.

8. Venture Capital: Betting on Asymmetric Upside and Unreasonable Founders.

“The working title I had for it was Risky Business, like the eighties movie. And then the chapter on Elon,” he said, “was ‘The Man Who Knew Nothing About Risk.’ ”

Long-term, asymmetric bets. Venture Capital (VC) is defined by a long time horizon and asymmetric payoffs: investments can lose 1x but return 10x, 100x, or more. This structure incentivizes VCs to take chances on high-upside, low-probability ideas.

Selecting founders. VCs often seek "unreasonable" founders who are deeply committed to a single, often contrarian, vision. These founders may be:

• Risk-ignorant or have a high tolerance for failure
• Driven by a "chip on their shoulder" or a desire for revenge
• Possessed of extreme confidence and stubbornness

Symbiosis and FOMO. The VC ecosystem involves a symbiosis between risk-tolerant VCs (often "foxes" who diversify bets) and risk-ignorant founders (often "hedgehogs" who go all-in on one idea). Despite their success, VCs are driven by FOMO, fearing missing out on the next big winner more than the risk of individual investment failures.

9. Crypto Bubbles: Fueled by FOMO, Memes, and Game Theory in an Unregulated Space.

“Poker is about skill. This is not about skill. This is just about getting on the bus. The bus showed up at the station. Most people did not get on the bus.”

A perfect storm. The crypto bubble of 2020-21 was fueled by:

• Boredom and anxiety during the pandemic
• Young men seeking quick wealth
• Fear of missing out (FOMO) on the "Next Big Thing"

Meme creation of value. Unlike traditional assets, the value of many crypto assets became detached from fundamentals, driven by online communities and viral memes. This created an "envy-based economy" where assets became focal points for collective coveting.

Game theory and scams. In an unregulated space, game theory dynamics like the prisoner's dilemma played out, incentivizing participants to hold assets as long as others did, despite the risk of collapse. This environment was ripe for scams and Ponzi schemes, exploiting investors' lack of financial literacy and desire for easy returns.

10. Effective Altruism and Rationalism: Applying Quantitative Rigor to Grand-World Problems.

“I think the overlap is in cognitive style,” said MacAskill. “People who are willing to take the idea of expected value seriously. People who are willing to kind of quantify the unquantifiable.”

Quantifying good. Effective Altruism (EA) and Rationalism are movements applying quantitative and probabilistic thinking to ethical and philosophical questions, particularly how to do the most good impartially. They share a cognitive style with other Riverians but focus on altruistic or grand-world problems.

Utilitarian leanings. EA often aligns with utilitarianism, seeking to maximize overall utility, even if it means making counterintuitive choices or quantifying things like the "value of a statistical life." This approach can be useful for policy decisions but raises complex ethical questions when applied to personal morality or infinite scenarios.

Differing streams. The movements encompass various interests, from global poverty and animal welfare (Singer stream) to futurism, AI, and prediction markets (Yudkowsky-Hanson stream). While sharing a common language of rationality, they differ in political orientation, ethical commitments, and willingness to challenge social taboos.

11. Sam Bankman-Fried's Downfall: A Cautionary Tale of Miscalculated Risk and Utilitarian Hubris.

“I think people are just kind of wimps and dismiss on principle options that involve going big,” he said.

Overwhelmed and overconfident. Sam Bankman-Fried's collapse was not due to a lack of intelligence but a combination of miscalculated risk, overconfidence, and a lack of judgment. He took on too much, too fast, in a complex, unregulated environment.

Utilitarian rationalization. SBF's strict utilitarian philosophy, believing the ends justified the means, may have rationalized extremely risky and unethical behavior. He viewed even potentially ruinous gambles as +EV if the theoretical upside was large enough, applying a distorted version of bet sizing principles like the Kelly criterion.

Failure of gatekeepers. SBF's rise was enabled by the trust placed in him by VCs and EAs, who overlooked warning signs due to his cultivated image and the allure of his potential wealth and influence. His downfall highlights the dangers of unchecked power and the need for rigorous due diligence, even for seemingly brilliant figures.

12. AI and Existential Risk: Humanity's Ultimate High-Stakes Gamble.

“We have spent two billion dollars on the greatest scientific gamble in history—and won,” said President Harry Truman, an avid poker player, in addressing the world after the bomb was dropped on Hiroshima less than three weeks later.

Accelerating progress. AI is advancing rapidly, driven by Silicon Valley's ethos of pushing technological boundaries. Unlike the government-led Manhattan Project, AI development is largely in the hands of private companies.

Existential stakes. Experts debate the likelihood of AI posing an existential risk (p(doom)), but even a small chance warrants serious consideration. Analogies to nuclear weapons highlight the potential for catastrophic outcomes from powerful technologies.

Navigating the future. The debate over AI risk involves differing reference classes and perspectives, from techno-optimism to doomerism. The future depends on humanity's ability to manage this high-stakes gamble, balancing progress with safety and developing institutions that can navigate the complex challenges ahead.

Last updated: May 3, 2025