kale

SunTzu Macchiaveli Greene

[alexei @alexeixbt]

bertrand russell drops a cold truth in this clip: good intentions don't make good decisions, game theory does.

it shows why two smart people making totally logical choices usually end up triggering the worst possible outcome for both in business, politics, and relationships.

how to stop asking "what should i do" and start reading hidden payoffs: key concepts below.

[AI_Explorer @ai_explorer25]

GOOGLE CEO SUNDAR PICHAI: "IF YOU DON'T LEARN HOW TO ORCHESTRATE AGENTS NOW, YOU'LL SPEND 2027 CATCHING UP TO PEOPLE WHO STARTED TODAY."

30 minutes on why the best engineers stopped writing code line by line and started orchestrating agents instead.

Most people think building an agent requires an engineering degree.

It doesn't.

It requires one guide and one afternoon.

Watch the interview. Then read the article below.

One guide. One afternoon. That's all it takes.

[Amit @HeyAmit_]

Instead of watching an hour of Netflix tonight.

This 1-hour Stanford lecture by Graham Weaver will completely change how you think about fear, courage, and why most people never unlock their true potential.

Bookmark it and give it 1 hour.

[Patrick J. Wolf @PatWolf]

Morning motivation

[Alok Kumar @Alokkumarzz]

Stop relying on short videos to learn how to make money
Ray Dalio explains wealth creation in 42 minutes
More solid than most content

[Eva Ai| Gate美股0费率 @Eva200699]

太震撼了！一小时顶两年MBA！

黄仁勋2011年斯坦福这场演讲，把创业、创新、公司重构的底层逻辑讲得清清楚楚，太值了

强烈推荐反复看

[MindArch @mindarchx]

Choongbum Lee, the math genius who cracked one of the hardest unsolved puzzles in modern probability:

"There's a specific way of splitting any random, unpredictable process into two simple pieces, one predictable, one pure chaos, and understanding that split is the closest thing to a cheat code for thinking about uncertainty."

this is the exact structure hiding underneath every model that claims to price risk in continuous time, and it's the first thing worth checking before trusting any strategy built on one.

cut through the notation and the split is precise. a stochastic differential equation says the tiny change in something at any instant equals a drift term, the direction it's heading on average, plus a volatility term multiplied by pure randomness, the noise shaking it away from that average path.

every continuous-time model in finance, no matter how complicated it looks on the surface, is built from exactly these two pieces.

that decomposition matters because it separates two completely different questions that get blurred together constantly, where is something heading on average, and how much is randomness capable of shoving it off that path at any given moment. conflating those two questions is exactly how people misprice risk, and exactly how you can catch someone else doing it too.

most people looking at a backtest or a pitch deck judge a strategy by how well its overall returns fit the past, without ever asking the sharper question, is the edge actually coming from correctly predicting the drift, or is it just getting lucky on the noise.

zoom out to how this plays out evaluating any strategy or signal someone shows you today. ask which of the two pieces it's actually claiming to predict, the average direction or the size of the randomness around it, and you'll immediately see whether the claim is even coherent, because most weak pitches quietly blur the two together to sound more impressive than they are.

this is exactly what "the strategy has strong historical returns" claims skip.

strong returns and correctly separating drift from noise are different achievements, and a strategy can show great numbers while secretly just riding noise it never actually understood.

the edge was never in the overall number. it was always in knowing which of the two pieces, the drift or the noise, you were actually right about.

Bookmark this alpha and follow @mindarchx for more gems.

[Lumen @lumenxbt]

Ten million people have watched an MIT professor accidentally destroy the executive coaching industry.

He filmed the lecture once in January 2018 and died eighteen months later.

Executive coaches charge fifteen thousand dollars a session to teach a third of what he covered in one hour for free.

His name was Patrick Winston. He ran the MIT Artificial Intelligence Laboratory from 1972 to 1997 and wrote the AI textbook every computer science major in the world read for thirty years.

Every January for four decades, he gave a lecture called "How to Speak."

His entire framework fits on a napkin.

Do not read. Be in the image. Keep images simple. Eliminate clutter. Start with an empathetic connection. End with a punch line the audience can repeat over dinner. Never open with a joke. Never end with "thank you."

That last rule alone has probably cost the executive coaching industry a hundred million dollars.

"Your success in life will be determined largely by your ability to speak, your ability to write, and the quality of your ideas. In that order."

That is the actual opening line of the lecture. Winston believed it strongly enough to spend fifty years teaching computer scientists how to talk.

Founders spend $80,000 on an MBA and then hire a communications coach to teach them the same material Winston filmed once for free. Engineers write brilliant code and lose promotions to teammates who watched this lecture on the train.

The lecture is free on MIT OpenCourseWare. The textbook is free on his page.

Winston died in 2019. Almost none of the ten million viewers have actually implemented the four rules on the napkin.

The napkin is free. The willingness to actually use it in your next meeting is the entire edge.

[Joseph Tsar @joseph_tsar_]

Full Course on How To Communicate Brilliantly (by Joseph Tsar)

[Param @ParamSiddh]

1. Algebra is good for problem-solving.

2. Geometry is good for visual thinking.

3. Calculus is good for understanding change.

4. Statistics is good for decision-making.

5. Number theory is good for logical discipline.

6. Linear algebra is good for modern science and engineering.

7. Discrete math is good for computer science.

8. Differential equations are good for modeling the real world.

9. Optimization is good for smart planning.

10. Graph theory is good for network thinking.

11. Set theory is good for structured reasoning.

12. Practice is good for mathematical fluency.

13. Curiosity is good for lifelong learning in math.

[Eva Ai| Gate美股0费率 @Eva200699]

25年前，李光耀在哈佛讲了一场两个半小时的领导力课

没有PPT，没有金句包装

后来很多人说：这场课，比读一个MBA更值

[aether @bluewdrift]

the best witchcraft i've learned is to say everything you're doing before you do it. even walking into a room. say "i'm walking into the kitchen and getting a drink," etc. after a couple of weeks, your mind has gotten used to doing what you say will happen. now your mind believes your words more and will more naturally work to make them happen.

[Eva Ai| Gate美股0费率 @Eva200699]

32岁的马斯克，2003年在斯坦福做了场45分钟闭门演讲，真的顶得上十本创业书

他直接把自己当时手里的三家公司——Zip2、PayPal、刚成立一年的SpaceX——从0到活下来的全过程，一层层拆给你看

怎么找方向、怎么控成本、怎么在几乎没钱的时候活下来、怎么用第一性原理拆问题

放到今天看，依然不过时

[MindArch @mindarchx]

Bill Chen, the mathematician who proved randomness itself could be turned into a repeatable, provable edge:

"There's one specific skill that got me hired at one of the biggest quant trading firms in the world, and once you actually learn to see it, you'll start noticing it in almost every decision you make with money."

this is the exact skill separating people who make decisions under uncertainty well from everyone else who's just guessing and calling it instinct.

cut through the poker table and the mechanism is almost elegant in its simplicity. instead of trying to memorize the correct response to every possible situation, the actual skill is learning to track how much you'd regret not having chosen each alternative, every single time, and slowly adjusting toward whatever choice keeps that regret lowest across many repeated decisions.

nobody hands you the winning strategy in advance. it emerges purely from paying close attention to your own past mistakes, over and over, until the mistakes become rare enough that nobody can consistently exploit you anymore.

most people make decisions under uncertainty by trusting a gut feeling in the moment, without ever going back to systematically check which past choices they'd actually regret if they had to make them again.

zoom out to how this plays out reviewing a trading decision after the fact on a desk today. tracking regret across many repeated decisions, not just whether a single trade won or lost, but whether a different choice would have consistently done better across similar situations, is exactly the discipline that separates a systematic edge from random noise dressed up as skill.

this is exactly what "trust your gut" advice skips. instinct built on unexamined outcomes and a strategy refined by systematically tracking regret across many repetitions are different things, and only one of them reliably converges toward something better over time.

the edge was never about knowing the right answer in advance. it was about paying close enough attention to your own mistakes that they eventually stopped happening.

Bookmark this gem and follow for more.

[Silverhand @21xSilverhand]

A Yale professor claims one law of physics decides everything that can and cannot happen in the universe. Drop an egg and it will never jump back into your hand, and nothing in Newton forbids it. Only this law does. His words.

2 million people started his course. Almost nobody made it to lecture 24, where he finally proves it.

The man is Ramamurti Shankar, and the way he teaches this is what makes the video worth it.

He opens with a 200 year old bet. An engineer named Carnot claimed no engine anyone ever builds can beat his. Two centuries later, no company in America, Japan or China has done it. Shankar shows why in ten minutes, by letting you build a better engine on the blackboard and then shooting it down.

Then the move that stays with you. He proves the law of the universe is not a command but a coin toss. Nothing forbids all the air in your room from rushing into one corner while you suffocate in the other. He writes down the odds of it. The number is why you are safe.

He ends with a formula so important it is carved on its author's tombstone in Vienna. Shankar says physicists visiting the city skip the concert halls and go read the stone.

His point for why this matters: the universe does not forbid the impossible. It just prices it.

[Di Krass @Di_Krass_]

"Every casino and hedge fund runs on one theorem you understand backwards. You lose ten bets and feel "due" to win. The coin doesn't care - the law of large numbers never rescues your losses, it drowns them."

Joe Blitzstein, Harvard statistics professor:

the trap: you lose ten bets in a row and feel "due." wrong: "the coin is memoryless. the coin does not care how many failures or how many losses you had before." early bad luck just gets swamped by sheer volume of trials.

that's the whole edge of the house and the fund: they don't win any single bet. a real, tiny advantage, repeated enough times, becomes near-certainty. the math doesn't correct your streak - it drowns it.

then the second theorem does something almost magical: "even if the original data did not look like they came from a normal distribution, when you average lots and lots of them, it looks normal." the bell curve under every risk model isn't an assumption - it's forced by this proof.

hedge funds pay for this information - here it's free, from zero. but one theorem isn't the edge. i'm pulling apart the whole toolkit a desk trades on - ruin, expectation, position sizing - one breakdown at a time. follow, and you'll read a market like the house reads a table.

[HCI-MCI @drhcimci]

Here’s the video for context

[Eva Ai| Gate美股0费率 @Eva200699]

别再靠短视频学怎么赚钱了
瑞·达利欧42分钟讲透财富创造
比大部分内容都扎实

[ooaes @21xooaes]

A NASA fellow claims 5 equations explain 99 percent of the physics that actually runs your world. Understand them deeply and you are set for life. His words.

And the way he does it is what makes the video worth it.

He does not teach the five as a list. He tells them as one story, where each equation is born from the one before it. F equals ma leads into gravity. Gravity rhymes with the law of electric charge, the exact same shape. That connects to magnetism. Magnetism folds into the wave. And the wave quietly opens the door to relativity and quantum physics.

By the end, all of physics feels like a single sentence written by one hand, not a pile of formulas you were forced to memorize.

The move that stays with you comes first. He says F equals ma is written the wrong way around, and rewrites it. One tiny flip, and the most famous equation on Earth suddenly means something school never told you.

His point for why this matters now: in the age of AI, the people who understand reality itself stay in demand. Everyone else is just memorizing.

Five equations. One thread. It is in the video.

[Incentivising @incentivising]

Game theory explains why working harder inside a broken system is the worst response to that system. Because a system is never truly broken. It's just producing exactly the outcomes its own incentive structures were designed to produce, whether intentional or not. Working harder inside this system increases your output in the payoff matrix, but it simply won't change the actual structure of the system's matrix. Thus, the correct response is not more effort. Instead, you must aim to identify whose interests the current structure serves and position yourself in favor of those interests rather than against them. Change the game, or play the game that is actually being played. Either way, you must stop optimizing for the game you wish it to be and start acting realistically.