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A MATHEMATICIAN WAS LAUGHED AT FOR STUDYING "ROUGHNESS" -- CLOUDS, COASTLINES, PRICES, THINGS TOO MESSY FOR REAL MATH. THEN HE SHOWED ONE TINY FORMULA, REPEATED, BUILDS INFINITE COMPLEXITY AND IT DESCRIBES REALITY BETTER THAN THE SMOOTH MATH EVERYONE WORSHIPPED 79 minutes from Benoit Mandelbrot at MIT, introduced by the... father of chaos theory. -> The idea that lands: the real world is not smooth. It is rough, jagged, self-repeating and that roughness has an exact mathematics, where one simple rule looped over itself spins out endless detail. A coastline, a fern, a stock chart -- zoom in and you find the same shape again, forever. Smooth equations are a polite lie we tell about a jagged world. Fractals are what reality actually looks like. This is how generative models work too -- simple operations repeated at scale until staggering complexity falls out. He found the principle decades before the machines. You thought messy meant random. This is the talk that shows messy has a law. Bookmark this. Watch it once, see patterns everywhere ↓show more

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$Benoit Mandelbrot, Yale professor, IBM Fellow, and inventor of fractals: "Every risk model at Citadel, Goldman and JPMorgan assumes markets are 'normal.' I proved they're wild. That one lie has vaporized hundreds of billions." this free TED talk is mandelbrot months before he died. almost every risk model treats the market as mild and smooth. he proved it's the opposite: rough, jagged, and wild, with extremes far more common than the bell curve allows. that gap is not academic. under the bell curve, the 2008 crash was a once-in-a-billion-years event. it happens roughly every decade. every VaR model that whispered "you're safe" and every fund that blew up in a week was trusting the same lie. those wild days also cluster together, which is exactly the "regime change" the thread is trying to catch. none of it is new. mandelbrot showed it in cotton prices in the 1960s, gave this talk for free, and wrote a whole book about it for the public. same lesson as my article: the math sat there for decades, ignored because it was inconvenient. here is what the regime thread won't admit. no model catches the wild day before it hits, its timing is unknowable by design. the edge isn't predicting the storm, it's sizing so a single wild day can never end you. the math is free. respecting the tails is the discipline almost nobody has.$

Benoit Mandelbrot, Yale professor, IBM Fellow, and inventor of fractals: "Every risk model at Citadel, Goldman and JPMorgan assumes markets are 'normal.' I proved they're wild. That one lie has vaporized hundreds of billions." this free TED talk is mandelbrot months before he died. almost every risk model treats the market as mild and smooth. he proved it's the opposite: rough, jagged, and wild, with extremes far more common than the bell curve allows. that gap is not academic. under the bell curve, the 2008 crash was a once-in-a-billion-years event. it happens roughly every decade. every VaR model that whispered "you're safe" and every fund that blew up in a week was trusting the same lie. those wild days also cluster together, which is exactly the "regime change" the thread is trying to catch. none of it is new. mandelbrot showed it in cotton prices in the 1960s, gave this talk for free, and wrote a whole book about it for the public. same lesson as my article: the math sat there for decades, ignored because it was inconvenient. here is what the regime thread won't admit. no model catches the wild day before it hits, its timing is unknowable by design. the edge isn't predicting the storm, it's sizing so a single wild day can never end you. the math is free. respecting the tails is the discipline almost nobody has.

Rossst.03

35,297 görüntüleme • 1 ay önce

Alan Oppenheim, MIT professor: "Jump Trading pays quants $650K to pull one real signal out of market noise. I wrote the textbook on that exact math and taught it for free." this free MIT lecture is the math the whole "quant edge" is built on, and almost nobody selling you a course will name it. the man teaching it wrote the signal-processing textbook every engineer on earth learned from, and he put the lectures online for nothing. here is the idea. a price chart is a signal buried in noise. most of what you see is random static, and hidden inside is a faint, repeating pattern with real mathematics for pulling it out. that is not a metaphor. jim simons was a codebreaker who did exactly this to enemy transmissions, then pointed the same math at the market and made a hundred billion dollars. none of it is new. oppenheim taught this in 1987, the math is older, and every lecture is free. same story i told in the article above. the edge was never a secret formula. it was knowing a market is a noisy signal, and having the tools to read it. here is what the gurus skip. the math to separate signal from noise is free and everyone has it. the edge is cleaner data than the next desk, and the discipline to trust a faint signal across thousands of trades instead of chasing the static. the filter is free. the patience to use it is not.

Alan Oppenheim, MIT professor: "Jump Trading pays quants $650K to pull one real signal out of market noise. I wrote the textbook on that exact math and taught it for free." this free MIT lecture is the math the whole "quant edge" is built on, and almost nobody selling you a course will name it. the man teaching it wrote the signal-processing textbook every engineer on earth learned from, and he put the lectures online for nothing. here is the idea. a price chart is a signal buried in noise. most of what you see is random static, and hidden inside is a faint, repeating pattern with real mathematics for pulling it out. that is not a metaphor. jim simons was a codebreaker who did exactly this to enemy transmissions, then pointed the same math at the market and made a hundred billion dollars. none of it is new. oppenheim taught this in 1987, the math is older, and every lecture is free. same story i told in the article above. the edge was never a secret formula. it was knowing a market is a noisy signal, and having the tools to read it. here is what the gurus skip. the math to separate signal from noise is free and everyone has it. the edge is cleaner data than the next desk, and the discipline to trust a faint signal across thousands of trades instead of chasing the static. the filter is free. the patience to use it is not.

Rossst.03

269,381 görüntüleme • 1 ay önce

IN 1999 MIT FILMED A MATH LECTURE ON THE ABSTRACT IDEA YOU PROBABLY HATED IN COLLEGE -- THE EXACT MATH GOOGLE LATER USED TO RANK THE ENTIRE INTERNET 50 minutes from Gilbert Strang, who taught this at MIT for over 60 years, on eigenvalues -- the one idea most students memorize and never understand. -> The shift it creates: an eigenvector is just the direction a system doesn't twist, only stretches. Find those, and a tangled mess of equations falls apart into something simple. You were drilled to compute them by hand and never told what they were for. Google's entire empire started here. PageRank is one giant eigenvector problem and the same math now sits inside PCA, recommendations, and how models find structure in data. Computing eigenvalues was never the skill -> understanding what they reveal is. This is where it finally clicks. Most people filed this under "Useless college math". The ones who watched this see it running quietly inside half the tech they touch. Bookmark & Watch it. This one's a legend ↓

IN 1999 MIT FILMED A MATH LECTURE ON THE ABSTRACT IDEA YOU PROBABLY HATED IN COLLEGE -- THE EXACT MATH GOOGLE LATER USED TO RANK THE ENTIRE INTERNET 50 minutes from Gilbert Strang, who taught this at MIT for over 60 years, on eigenvalues -- the one idea most students memorize and never understand. -> The shift it creates: an eigenvector is just the direction a system doesn't twist, only stretches. Find those, and a tangled mess of equations falls apart into something simple. You were drilled to compute them by hand and never told what they were for. Google's entire empire started here. PageRank is one giant eigenvector problem and the same math now sits inside PCA, recommendations, and how models find structure in data. Computing eigenvalues was never the skill -> understanding what they reveal is. This is where it finally clicks. Most people filed this under "Useless college math". The ones who watched this see it running quietly inside half the tech they touch. Bookmark & Watch it. This one's a legend ↓

slash1s

38,161 görüntüleme • 1 ay önce

IN 1986 MIT FILMED THE LECTURE WHERE CODE STOPPED BEING CODE AND BECAME DATA 43 minutes from Gerald Sussman, in the most legendary intro programming course ever recorded. -> The idea that lands: to a program, your code is just data it can read and rewrite. He builds a program that does real calculus -- not by crunching numbers, but by reading the math as a list and transforming it piece by piece. Then he shows the trick hiding under all of it: in this language, code and data are the same material. Forty years later that is exactly what an AI coding agent is -- a program that reads your code as data, rewrites it, and hands it back. Sussman drew the whole idea on a blackboard in 1986. Writing code was never the deepest skill -- understanding that code itself is data a program can manipulate is. This is where you learn it. Most people think AI writing code is brand new. The ones who watch this saw the blueprint 40 years ago. Bookmark & Watch it. This one's a legend ↓

slash1s

22,107 görüntüleme • 1 ay önce

In 1963, Benoit Mandelbrot showed that cotton prices don't follow a bell curve. He showed it again with wheat, interest rates, stocks, and indices. Wall Street thanked him, gave him a medal, and kept using the bell curve. Every fund blowup since has been the invoice. Mandelbrot wasn't a Wall Street insider. He was a mathematician at IBM, an outsider the economics establishment spent 40 years trying to bury. Most of his career, mainstream finance journals wouldn't touch him. He was right anyway. The graveyard of blown-up funds keeps proving it. The thread above sells you a better filter. Mandelbrot spent his life on the assumption underneath every filter, the one every filter salesman needs you not to question. The assumption is that price moves cluster near the average and big moves are almost impossible. Every Sharpe ratio, every VaR, every risk model in every fund quietly runs on it. Mandelbrot proved for four decades, in papers Wall Street chose not to read, that real markets have fat tails, wild variance, and rough repeating patterns at every scale. The 10-sigma move isn't once in a hundred lifetimes. In markets, it shows up on a Tuesday. The self-similarity part is the tell. Take a crypto chart and cover the axis labels. You cannot tell if you're looking at a one-minute or a one-year timeframe. The roughness looks the same because the underlying process is the same. It does not average out at longer horizons. It just repeats. This is why every model that promises the tail is 1-in-10,000 blows up on schedule. LTCM died in 1998 and the industry called it once-a-millennium. 2008 repeated it a decade later. Crypto compresses the same lesson into weeks. 3AC, Luna, FTX, every leveraged desk that went to zero on a weekend was running on the bell curve Mandelbrot buried in 1963. The takeaway isn't that filters are useless. It's that no filter tells you how much to bet when it's right. Sizing is what survives the tail. The filter tells you where to look. Sizing decides whether you're still alive to look tomorrow. Build the filter. Build the swarm. Build the sharpest model of your generation. Just remember they're all fitting a world that doesn't exist, and the part that survives the tail, that part, you still have to bring yourself. His TED talk is from 2010. It's free. It was free in 1963 too.

In 1963, Benoit Mandelbrot showed that cotton prices don't follow a bell curve. He showed it again with wheat, interest rates, stocks, and indices. Wall Street thanked him, gave him a medal, and kept using the bell curve. Every fund blowup since has been the invoice. Mandelbrot wasn't a Wall Street insider. He was a mathematician at IBM, an outsider the economics establishment spent 40 years trying to bury. Most of his career, mainstream finance journals wouldn't touch him. He was right anyway. The graveyard of blown-up funds keeps proving it. The thread above sells you a better filter. Mandelbrot spent his life on the assumption underneath every filter, the one every filter salesman needs you not to question. The assumption is that price moves cluster near the average and big moves are almost impossible. Every Sharpe ratio, every VaR, every risk model in every fund quietly runs on it. Mandelbrot proved for four decades, in papers Wall Street chose not to read, that real markets have fat tails, wild variance, and rough repeating patterns at every scale. The 10-sigma move isn't once in a hundred lifetimes. In markets, it shows up on a Tuesday. The self-similarity part is the tell. Take a crypto chart and cover the axis labels. You cannot tell if you're looking at a one-minute or a one-year timeframe. The roughness looks the same because the underlying process is the same. It does not average out at longer horizons. It just repeats. This is why every model that promises the tail is 1-in-10,000 blows up on schedule. LTCM died in 1998 and the industry called it once-a-millennium. 2008 repeated it a decade later. Crypto compresses the same lesson into weeks. 3AC, Luna, FTX, every leveraged desk that went to zero on a weekend was running on the bell curve Mandelbrot buried in 1963. The takeaway isn't that filters are useless. It's that no filter tells you how much to bet when it's right. Sizing is what survives the tail. The filter tells you where to look. Sizing decides whether you're still alive to look tomorrow. Build the filter. Build the swarm. Build the sharpest model of your generation. Just remember they're all fitting a world that doesn't exist, and the part that survives the tail, that part, you still have to bring yourself. His TED talk is from 2010. It's free. It was free in 1963 too.

Veles

44,581 görüntüleme • 27 gün önce

Alan Oppenheim, MIT professor: "Every trader alive uses a moving average. Almost none of them know it's a filter, and funds pay quants $600K for the version they were never taught." a moving average is a filter. it smooths a jumpy price to reveal the slower signal hiding underneath. that is all it is, and it is the bluntest one there is. the same math gives you filters that lag less and cut more noise, and that gap is a real edge. this is the second half of what Simons was doing. first you accept the market is a signal buried in noise. then you build the filter that reads it, and the moving average on your chart is the crudest possible version. Oppenheim builds the real ones at the board in this lecture. here is the catch. a filter only helps if there is a real signal under the noise. smooth pure randomness and you will see a beautiful trend that means nothing. the filter is free. knowing there is a real signal worth filtering is the edge.

Alan Oppenheim, MIT professor: "Every trader alive uses a moving average. Almost none of them know it's a filter, and funds pay quants $600K for the version they were never taught." a moving average is a filter. it smooths a jumpy price to reveal the slower signal hiding underneath. that is all it is, and it is the bluntest one there is. the same math gives you filters that lag less and cut more noise, and that gap is a real edge. this is the second half of what Simons was doing. first you accept the market is a signal buried in noise. then you build the filter that reads it, and the moving average on your chart is the crudest possible version. Oppenheim builds the real ones at the board in this lecture. here is the catch. a filter only helps if there is a real signal under the noise. smooth pure randomness and you will see a beautiful trend that means nothing. the filter is free. knowing there is a real signal worth filtering is the edge.

Rossst.03

214,907 görüntüleme • 1 ay önce

Elon Musk reduced the oldest question in human history to basic math. No one has found a flaw in it. Musk: “What are the odds that we are in base reality? And that this has not happened before.” You don’t need a physics degree to follow it. You need a timeline. Musk: “If you look at the advancement of video games, it’s gone from Pong, two rectangles and a square batting it back and forth, to photorealistic, real-time games with millions of people playing simultaneously.” Fifty years. That is all it took to close the gap between two rectangles on a screen and a world you cannot tell apart from the one outside your window. Musk: “If that trend continues, video games will be indistinguishable from reality.” The visuals are not what seals it. The intelligence is. Musk: “Think of how sophisticated the conversations are you can have with an AI today, and that’s only going to get more sophisticated.” We are not scripting characters anymore. We are building minds that reason, adapt, and surprise the people who made them. We are nowhere near finished. Musk: “The future, if civilization continues, will be millions, maybe billions of photorealistic, indistinguishable from reality, video games. And with characters in those video games that are very deep, and where the dialogue is not pre-programmed.” One base reality. Billions of perfect copies. Each one running minds that feel exactly as conscious as you do right now. Each one certain it is the original. Musk: “So then what are the odds that we are in base reality?” If even one civilization crosses that threshold, simulated minds outnumber real ones by billions. The probability you are sitting in the real one is not low. It is nearly zero. Not as philosophy. As mathematics. We are not watching this happen. We are building it. Right now. Every AI that reasons without a script. Every world rendered one frame closer to indistinguishable. We are constructing the exact technology that makes our own existence statistically implausible. And we will never stop. Because the curiosity that questions reality is the same force that builds it. If the math holds, something built us. Something conscious enough to create consciousness. They stood where we are standing. Same question. Same inability to stop. And whatever built them never answered it either. There is no top floor. There is no original. None of that changes what you feel right now. Consciousness was never about what you are made of. It was about what you experience. Musk did not float a theory. He held up a mirror with no back wall. And the math does not need you to believe it. It only needs time.

Elon Musk reduced the oldest question in human history to basic math. No one has found a flaw in it. Musk: “What are the odds that we are in base reality? And that this has not happened before.” You don’t need a physics degree to follow it. You need a timeline. Musk: “If you look at the advancement of video games, it’s gone from Pong, two rectangles and a square batting it back and forth, to photorealistic, real-time games with millions of people playing simultaneously.” Fifty years. That is all it took to close the gap between two rectangles on a screen and a world you cannot tell apart from the one outside your window. Musk: “If that trend continues, video games will be indistinguishable from reality.” The visuals are not what seals it. The intelligence is. Musk: “Think of how sophisticated the conversations are you can have with an AI today, and that’s only going to get more sophisticated.” We are not scripting characters anymore. We are building minds that reason, adapt, and surprise the people who made them. We are nowhere near finished. Musk: “The future, if civilization continues, will be millions, maybe billions of photorealistic, indistinguishable from reality, video games. And with characters in those video games that are very deep, and where the dialogue is not pre-programmed.” One base reality. Billions of perfect copies. Each one running minds that feel exactly as conscious as you do right now. Each one certain it is the original. Musk: “So then what are the odds that we are in base reality?” If even one civilization crosses that threshold, simulated minds outnumber real ones by billions. The probability you are sitting in the real one is not low. It is nearly zero. Not as philosophy. As mathematics. We are not watching this happen. We are building it. Right now. Every AI that reasons without a script. Every world rendered one frame closer to indistinguishable. We are constructing the exact technology that makes our own existence statistically implausible. And we will never stop. Because the curiosity that questions reality is the same force that builds it. If the math holds, something built us. Something conscious enough to create consciousness. They stood where we are standing. Same question. Same inability to stop. And whatever built them never answered it either. There is no top floor. There is no original. None of that changes what you feel right now. Consciousness was never about what you are made of. It was about what you experience. Musk did not float a theory. He held up a mirror with no back wall. And the math does not need you to believe it. It only needs time.

Dustin

193,350 görüntüleme • 27 gün önce

A PHYSICS PROFESSOR GAVE THE SAME LECTURE 1,742 TIMES TO WARN ABOUT ONE IDEA QUIETLY BREAKING THE HUMAN RACE. IT IS THE WORD EVERY AI LAB THROWS AROUND TODAY AND ALMOST NONE OF THEM ACTUALLY UNDERSTAND IT. 72 minutes from Albert Bartlett, a University of Colorado physicist, on the one piece of math he called humanity's greatest blind spot. -> The idea that lands: a small steady percentage is never small. 7% a year sounds calm, but it doubles in a decade, doubles again in the next, and quietly runs away from you. He shows it with bacteria in a bottle, with money, with whole cities -- the same curve that looks flat for ages and then explodes almost overnight. Everyone calls that curve "Exponential". He proves most people hear it as "Fast" when it actually means something far more violent. Right now every lab and every headline calls AI exponential. This is the talk that shows you what the word truly does -- so you see both the hype and the real danger the way the math demands. You thought it was a boring math word. It was the whole story the entire time. Save this one. You'll never hear "Exponential" the same way ↓

A PHYSICS PROFESSOR GAVE THE SAME LECTURE 1,742 TIMES TO WARN ABOUT ONE IDEA QUIETLY BREAKING THE HUMAN RACE. IT IS THE WORD EVERY AI LAB THROWS AROUND TODAY AND ALMOST NONE OF THEM ACTUALLY UNDERSTAND IT. 72 minutes from Albert Bartlett, a University of Colorado physicist, on the one piece of math he called humanity's greatest blind spot. -> The idea that lands: a small steady percentage is never small. 7% a year sounds calm, but it doubles in a decade, doubles again in the next, and quietly runs away from you. He shows it with bacteria in a bottle, with money, with whole cities -- the same curve that looks flat for ages and then explodes almost overnight. Everyone calls that curve "Exponential". He proves most people hear it as "Fast" when it actually means something far more violent. Right now every lab and every headline calls AI exponential. This is the talk that shows you what the word truly does -- so you see both the hype and the real danger the way the math demands. You thought it was a boring math word. It was the whole story the entire time. Save this one. You'll never hear "Exponential" the same way ↓

slash1s

100,138 görüntüleme • 1 ay önce

We often hear that machine learning models "learn patterns in data". But what does that actually look like in geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a self-organizing map...a simple unsupervised neural model...learn the shape of a two-dimensional dataset arranged in a spiral arm. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud...it knows nothing about the structure underneath. Learning is a repeated game: pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML

We often hear that machine learning models "learn patterns in data". But what does that actually look like in geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a self-organizing map...a simple unsupervised neural model...learn the shape of a two-dimensional dataset arranged in a spiral arm. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud...it knows nothing about the structure underneath. Learning is a repeated game: pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML

Mathelirium

139,682 görüntüleme • 8 ay önce

We often hear that Machine Learning models learn patterns in data. But what does that actually look like in Geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a Self-Organizing Map (SOM), a simple unsupervised neural model, learn the shape of a 3D datasets l, one static and the other dynamic. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud. It knows nothing about the structure underneath. Learning is a repeated game: Pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. Python code is available for Subscribers. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML

We often hear that Machine Learning models learn patterns in data. But what does that actually look like in Geometry? If you dropped a little elastic mesh into a cloud of points and let it learn, how would it fold itself to match the shape of the data? In this scene we watch a Self-Organizing Map (SOM), a simple unsupervised neural model, learn the shape of a 3D datasets l, one static and the other dynamic. On top of this, we lay down a square grid of neurons whose weights live in the same plane. At the start, this grid is just a flat net floating across the cloud. It knows nothing about the structure underneath. Learning is a repeated game: Pick a random data point, find the neuron whose weight is closest, and then nudge that neuron and its neighbours toward the point. Do this again and again, while slowly shrinking how far the neighbourhood influence spreads. Python code is available for Subscribers. #MachineLearning #ManifoldLearning #UnsupervisedLearning #NeuralMaps #GeometricML

Mathelirium

76,194 görüntüleme • 5 ay önce

Marvin Minsky, the MIT scientist who founded AI: "Citadel pays PhDs $500K to find the perfect equation. The market doesn't have one. It's beaten by a swarm of dumb agents, the exact design Marvin Minsky said your brain runs on." the thread above is about swarm intelligence, letting a crowd of simple agents search the ugly, shifting landscape of a market that no clean equation can solve. minsky's entire life's work says that isn't a hack. it is how intelligence itself is built. he proved you don't need a smart central solver. you need many mindless specialists, each doing one tiny job, none understanding the whole. connect enough of them and something intelligent emerges from parts that are individually dumb. a market is exactly that: millions of simple agents, no one in charge, collectively solving a problem none of them can see. that is why the swarm beats the elegant math. a single closed-form equation assumes a clean, stable world. the market is nonlinear, non-stationary, full of traps. a swarm doesn't need to understand the landscape, it explores it from a thousand angles at once and can't get permanently stuck where one clever model would. minsky saw this in the mind decades before quants borrowed it for markets. he taught it at MIT, for free, in this lecture. same story i keep telling: the "new" AI idea running the funds is an old idea in a new wrapper. here is what the thread underplays, and minsky knew it. a swarm is only as good as how its agents are wired and rewarded. connect them wrong and a thousand dumb agents don't become a genius, they become expensive noise that overfits and blows up. the swarm is free. the architecture, knowing how to connect and constrain the agents, is the entire edge.

Marvin Minsky, the MIT scientist who founded AI: "Citadel pays PhDs $500K to find the perfect equation. The market doesn't have one. It's beaten by a swarm of dumb agents, the exact design Marvin Minsky said your brain runs on." the thread above is about swarm intelligence, letting a crowd of simple agents search the ugly, shifting landscape of a market that no clean equation can solve. minsky's entire life's work says that isn't a hack. it is how intelligence itself is built. he proved you don't need a smart central solver. you need many mindless specialists, each doing one tiny job, none understanding the whole. connect enough of them and something intelligent emerges from parts that are individually dumb. a market is exactly that: millions of simple agents, no one in charge, collectively solving a problem none of them can see. that is why the swarm beats the elegant math. a single closed-form equation assumes a clean, stable world. the market is nonlinear, non-stationary, full of traps. a swarm doesn't need to understand the landscape, it explores it from a thousand angles at once and can't get permanently stuck where one clever model would. minsky saw this in the mind decades before quants borrowed it for markets. he taught it at MIT, for free, in this lecture. same story i keep telling: the "new" AI idea running the funds is an old idea in a new wrapper. here is what the thread underplays, and minsky knew it. a swarm is only as good as how its agents are wired and rewarded. connect them wrong and a thousand dumb agents don't become a genius, they become expensive noise that overfits and blows up. the swarm is free. the architecture, knowing how to connect and constrain the agents, is the entire edge.

Rossst.03

45,307 görüntüleme • 25 gün önce

A NASA fellow claims the modern world runs on one equation. Your phone signal, wifi, satellites, this post reaching your screen. All of it obeys one line of math written in the 1860s, before the light bulb existed. His words. The man is Ali Alqaraghuli, a former NASA postdoctoral fellow who now runs two hardware companies. And the way he teaches it is what makes the video worth it. He does not derive the equation. He teaches you to read it. His claim is that school taught you to read math wrong, and one symbol proves it: what you were told is a plus sign is actually something else. Once you see it, the whole equation turns from notation into a sentence. Then he uses that sentence to walk you through how a signal actually gets from your phone to a satellite and back. One viewer called that section straight up magic. It is 4 minutes of it. The comments are the proof. A physics student wrote it explained what a semester with his professor could not. An electrical engineer admitted this is where the equations finally clicked. One person wrote: I cried and I do not even know why. His larger point: the wireless world is not magic and never was. It is one readable line, and reading it is a skill nobody bothered to teach you. One equation. Everything wireless. 14 minutes. It is in the video.

A NASA fellow claims the modern world runs on one equation. Your phone signal, wifi, satellites, this post reaching your screen. All of it obeys one line of math written in the 1860s, before the light bulb existed. His words. The man is Ali Alqaraghuli, a former NASA postdoctoral fellow who now runs two hardware companies. And the way he teaches it is what makes the video worth it. He does not derive the equation. He teaches you to read it. His claim is that school taught you to read math wrong, and one symbol proves it: what you were told is a plus sign is actually something else. Once you see it, the whole equation turns from notation into a sentence. Then he uses that sentence to walk you through how a signal actually gets from your phone to a satellite and back. One viewer called that section straight up magic. It is 4 minutes of it. The comments are the proof. A physics student wrote it explained what a semester with his professor could not. An electrical engineer admitted this is where the equations finally clicked. One person wrote: I cried and I do not even know why. His larger point: the wireless world is not magic and never was. It is one readable line, and reading it is a skill nobody bothered to teach you. One equation. Everything wireless. 14 minutes. It is in the video.

ooaes

28,458 görüntüleme • 11 gün önce

Persi Diaconis, Stanford mathematician and former professional magician: "I spent fifty years proving one thing: almost nothing is as random as it looks. The 50.75% that built Renaissance wasn't luck. It was a tiny crack in the randomness, found and repeated a million times." this free lecture holds the exact idea the thread above is built on. and the man giving it isn't a trader. he's a stanford professor and former professional magician who spent his career on one question: where does real randomness end, and where does a hidden edge begin. here is his life's finding. a coin, a shuffle, a market, all look random, yet each hides a faint, measurable bias. on its own that bias is nothing, indistinguishable from luck. repeat it enough times and it stops being luck and becomes a law. that faint crack, found and repeated, is the whole distance between a 50.75% win rate and a hundred billion dollars. none of this is new or hidden. diaconis has taught it for decades, the math runs back to 1713, and the lecture is free. i mapped the full system in my article, expected value, kelly, and this. same point the thread makes: the edge was sitting in plain sight. here is the part the gurus skip. a faint edge only pays if you survive long enough to reach it, and that takes correct sizing and the patience to trust it through thousands of losing-looking trades. most quit while it still looks like randomness. the math is free. the nerve to hold it is the edge.

Persi Diaconis, Stanford mathematician and former professional magician: "I spent fifty years proving one thing: almost nothing is as random as it looks. The 50.75% that built Renaissance wasn't luck. It was a tiny crack in the randomness, found and repeated a million times." this free lecture holds the exact idea the thread above is built on. and the man giving it isn't a trader. he's a stanford professor and former professional magician who spent his career on one question: where does real randomness end, and where does a hidden edge begin. here is his life's finding. a coin, a shuffle, a market, all look random, yet each hides a faint, measurable bias. on its own that bias is nothing, indistinguishable from luck. repeat it enough times and it stops being luck and becomes a law. that faint crack, found and repeated, is the whole distance between a 50.75% win rate and a hundred billion dollars. none of this is new or hidden. diaconis has taught it for decades, the math runs back to 1713, and the lecture is free. i mapped the full system in my article, expected value, kelly, and this. same point the thread makes: the edge was sitting in plain sight. here is the part the gurus skip. a faint edge only pays if you survive long enough to reach it, and that takes correct sizing and the patience to trust it through thousands of losing-looking trades. most quit while it still looks like randomness. the math is free. the nerve to hold it is the edge.

Rossst.03

229,785 görüntüleme • 1 ay önce

Persi Diaconis walked into a lecture at the University of Washington, held up a coin, and told a room of physicists that Richard Feynman was fooled by it his entire life. He was right. In 2007, Diaconis proved a coin flip is not 50/50. It lands on the side it started on about 51 percent of the time. The bias comes from the physics of rotation under gravity. Every physicist since Newton had assumed 50/50 without ever testing it. Every trading model built on that assumption is running on the same lie. The lecture was on Feynman's book "The Meaning of it All." Diaconis quoted the most famous line in it: "the first principle is that you must not fool yourself, and you are the easiest person to fool." Then he pointed out that Feynman himself was fooled by every coin he ever flipped. Feynman's own rule would have killed the 50/50 assumption on day one. The market is the same setup at scale. Every model that assumes independent 50/50 outcomes at the base layer is built on a physical impossibility. Order flow, positioning, forced flows, expiries all leave biases larger than 1 percent. Your gut cannot see them. The math already knows they are there. Diaconis's rule: before you trust a random process, check it. Actually check it. Not with a simulation. With a proof or an experiment. The coin is where you start. The chart is where the same rule pays. The only random thing about markets is how thoroughly you refuse to check them.

Persi Diaconis walked into a lecture at the University of Washington, held up a coin, and told a room of physicists that Richard Feynman was fooled by it his entire life. He was right. In 2007, Diaconis proved a coin flip is not 50/50. It lands on the side it started on about 51 percent of the time. The bias comes from the physics of rotation under gravity. Every physicist since Newton had assumed 50/50 without ever testing it. Every trading model built on that assumption is running on the same lie. The lecture was on Feynman's book "The Meaning of it All." Diaconis quoted the most famous line in it: "the first principle is that you must not fool yourself, and you are the easiest person to fool." Then he pointed out that Feynman himself was fooled by every coin he ever flipped. Feynman's own rule would have killed the 50/50 assumption on day one. The market is the same setup at scale. Every model that assumes independent 50/50 outcomes at the base layer is built on a physical impossibility. Order flow, positioning, forced flows, expiries all leave biases larger than 1 percent. Your gut cannot see them. The math already knows they are there. Diaconis's rule: before you trust a random process, check it. Actually check it. Not with a simulation. With a proof or an experiment. The coin is where you start. The chart is where the same rule pays. The only random thing about markets is how thoroughly you refuse to check them.

veles

18,798 görüntüleme • 24 gün önce

IN 1986 MIT FILMED A LECTURE THAT OPENS BY TELLING YOU COMPUTER SCIENCE IS NOT A SCIENCE AND HAS ALMOST NOTHING TO DO WITH COMPUTERS 72 minutes from Hal Abelson and Gerald Sussman, the lecture an entire generation of engineers calls the one that rewired how they think. -> The line that lands: computer science is about computers the way astronomy is about telescopes. The tool was never the point. The real subject was always one thing -- controlling complexity. Everything else is detail. Forty years later it reads like a prophecy. AI writes the syntax now. What's left is exactly what they taught: taming complexity nobody can hold in their head. The language was never the skill -> the thinking was. This is where you learn it. Most people chase the newest framework. The ones who watched this think on a level frameworks can't touch. Bookmark & Watch today it, this one's a legend ↓

IN 1986 MIT FILMED A LECTURE THAT OPENS BY TELLING YOU COMPUTER SCIENCE IS NOT A SCIENCE AND HAS ALMOST NOTHING TO DO WITH COMPUTERS 72 minutes from Hal Abelson and Gerald Sussman, the lecture an entire generation of engineers calls the one that rewired how they think. -> The line that lands: computer science is about computers the way astronomy is about telescopes. The tool was never the point. The real subject was always one thing -- controlling complexity. Everything else is detail. Forty years later it reads like a prophecy. AI writes the syntax now. What's left is exactly what they taught: taming complexity nobody can hold in their head. The language was never the skill -> the thinking was. This is where you learn it. Most people chase the newest framework. The ones who watched this think on a level frameworks can't touch. Bookmark & Watch today it, this one's a legend ↓

slash1s

361,389 görüntüleme • 1 ay önce

I've become a missionary with one message. Every time I meet a young person, the same words: have children, get married, build a family. I did not decide on this calling. It overtook me. And it overtook me for a single reason. I had no idea. I genuinely did not understand how much joy, how much meaning, how much sheer beauty pours out of a child until I was holding one of my own and felt the floor of my life drop into something deeper than I knew was there. I grew up white, affluent, secular, comfortable, and insulated. That world does not put babies in front of you. None of my friends were starting families. Out of my whole circle, almost no one has a big one. We were not formed by the presence of children. We were formed by their absence, by the strange quiet of homes built for two careers and no cradle. And a person believes what his world shows him. So we believed. What we believed was a lie. It is a lie with an author, and that the author is the enemy of joy himself. It is the gospel of the world, and its commandment is wait. Wait until you are older. Wait until the career is built and the savings are stacked and the twenties are properly spent. Enjoy your freedom. You are not ready. It does not arrive sounding like temptation. It arrives sounding like wisdom, like prudence, like the responsible thing, and that is exactly why it works. The most effective lies are the ones that wear the face of virtue. And the maddening thing is that it collapses from every angle at once. It is not rooted in biology, because the body is made for this work precisely in the years we are told to postpone it. The flesh keeps a calendar the culture pretends not to see. And it is not rooted in theology either. You will not find this deferral anywhere in the Christian imagination, in any of the fathers, in any of the scriptures. So choose whatever lens you like. Take the cold secular measure or the ancient sacred one. By either light the counsel is rotten. It is bad for the body and bad for the soul and bad for the society downstream of both. This is why I have come to see it as one of the central tragedies of my generation. Every age carries its own wound. The Great Depression was a depression of bread, a scarcity in the world of matter, hunger you could measure. Ours is a depression of a different order. It is a famine of the spirit in the middle of abundance. We have more than any people who ever lived and we are starving in a way our ancestors would not recognize, because the thing we are refusing cannot be bought and cannot be banked. The ones most made to give and receive this love are quietly declining it. They are walking away from the one inheritance that actually compounds, and the cruelest part is that they do not feel the loss as loss. You cannot grieve what you were taught not to want. That is the deepest cut of it. The lie does not only steal the thing. It steals the capacity to know the thing was stolen. A man can spend his whole life on the far side of a door he never knew was a door, mistaking the wall for the edge of the world. Because this beauty is not ordinary beauty. It is not the pleasure of a good meal or a clear morning. It is participation in something that comes down from above, the same generative love that spoke everything out of nothing and called it good. To make a person, to be undone and remade by loving that person more than your own life, is to be drawn for a moment inside the very act that holds the cosmos together. A child does not merely add to your life. A child reorders the soul. It teaches you what you are by asking everything of you, and you discover, kneeling there exhausted at three in the morning, that you had a capacity for self gift you never suspected, a depth in yourself you had no other way to reach. In the Gospel of John, on the last night, Jesus prays, these things I have spoken to you that my joy may be in you, and that your joy may be complete. And I have come to understand why family is the road into that fullness, why it is not one path among many but the one most fitted to the shape of the promise. Consider who is praying. Christ does not come to us as a lone figure dropped out of the sky. He comes out of a family older than the world, the eternal communion of Father and Son, the love between them so total and so alive that theologians dared to call it a third person. Before there was anything, there was a family. The deepest fact about reality is not a force or a law or a void. It is a household. It is begetting and being begotten, giving and receiving, a Father who is only a Father because there is a Son. So when Jesus speaks of joy made complete, he is not pointing away from family toward something higher. He is pointing toward the very thing he came from, the life he has known from eternity and came to share. His joy is the joy of belonging utterly to a Father and pouring himself out for those he loves. When you marry, when you bring a child into the world, when you wear yourself down in the small unseen labors of a home, you are not stepping outside that divine life. You are stepping into a small image of it. Your family is a created echo of an uncreated one. The love you give your child rhymes with the love the Father has for the Son. The exhaustion, the tenderness, the way a parent would tear the sky open to protect a sleeping infant, all of it is the heavens pressed faintly into flesh, the eternal household leaving its fingerprint on yours. That is why the joy is not merely added to family but completed in it. We were made in the image of a God who is, at his very root, relation and gift and generation. To found a family is to do the most Godlike thing a creature can do, to participate from below in the begetting that God does from all eternity. Your home becomes a window. Through it, dimly and imperfectly, you glimpse the country you came from and are going to. And now a word for the young people reading this, the ones who do not yet have children. I want to tell you what it is like from where I stand. When I am out somewhere, a restaurant, anywhere, and a large family comes through the door, the noise and the chaos and the small bodies of them, something happens in me on two levels at once. The first is joy. A pure gladness at the sight, the way you feel watching something good and alive. But underneath it, almost in the same instant, a sadness reaches up and takes hold of my heart. Because I know now, at my age, after my own years of waiting, that I will never have that. I will never know the particular fruit of a family that large, the fullness of that table, the weight of all those lives gathered under one roof. The door to it has quietly closed, and I felt it close. And I am telling you plainly, because I love you and have no reason to lie to you: you will feel this too. You will. The day will come when you see what you passed up, and you will recognize the ache for what it is, and it will be too late to answer it. So please, learn from a man who got it wrong. Let my regret be worth something by becoming your wisdom. Do not wait yourself into a grief you cannot undo. Choose now, while the door is open, so that you may step into a joy that does not end.

I've become a missionary with one message. Every time I meet a young person, the same words: have children, get married, build a family. I did not decide on this calling. It overtook me. And it overtook me for a single reason. I had no idea. I genuinely did not understand how much joy, how much meaning, how much sheer beauty pours out of a child until I was holding one of my own and felt the floor of my life drop into something deeper than I knew was there. I grew up white, affluent, secular, comfortable, and insulated. That world does not put babies in front of you. None of my friends were starting families. Out of my whole circle, almost no one has a big one. We were not formed by the presence of children. We were formed by their absence, by the strange quiet of homes built for two careers and no cradle. And a person believes what his world shows him. So we believed. What we believed was a lie. It is a lie with an author, and that the author is the enemy of joy himself. It is the gospel of the world, and its commandment is wait. Wait until you are older. Wait until the career is built and the savings are stacked and the twenties are properly spent. Enjoy your freedom. You are not ready. It does not arrive sounding like temptation. It arrives sounding like wisdom, like prudence, like the responsible thing, and that is exactly why it works. The most effective lies are the ones that wear the face of virtue. And the maddening thing is that it collapses from every angle at once. It is not rooted in biology, because the body is made for this work precisely in the years we are told to postpone it. The flesh keeps a calendar the culture pretends not to see. And it is not rooted in theology either. You will not find this deferral anywhere in the Christian imagination, in any of the fathers, in any of the scriptures. So choose whatever lens you like. Take the cold secular measure or the ancient sacred one. By either light the counsel is rotten. It is bad for the body and bad for the soul and bad for the society downstream of both. This is why I have come to see it as one of the central tragedies of my generation. Every age carries its own wound. The Great Depression was a depression of bread, a scarcity in the world of matter, hunger you could measure. Ours is a depression of a different order. It is a famine of the spirit in the middle of abundance. We have more than any people who ever lived and we are starving in a way our ancestors would not recognize, because the thing we are refusing cannot be bought and cannot be banked. The ones most made to give and receive this love are quietly declining it. They are walking away from the one inheritance that actually compounds, and the cruelest part is that they do not feel the loss as loss. You cannot grieve what you were taught not to want. That is the deepest cut of it. The lie does not only steal the thing. It steals the capacity to know the thing was stolen. A man can spend his whole life on the far side of a door he never knew was a door, mistaking the wall for the edge of the world. Because this beauty is not ordinary beauty. It is not the pleasure of a good meal or a clear morning. It is participation in something that comes down from above, the same generative love that spoke everything out of nothing and called it good. To make a person, to be undone and remade by loving that person more than your own life, is to be drawn for a moment inside the very act that holds the cosmos together. A child does not merely add to your life. A child reorders the soul. It teaches you what you are by asking everything of you, and you discover, kneeling there exhausted at three in the morning, that you had a capacity for self gift you never suspected, a depth in yourself you had no other way to reach. In the Gospel of John, on the last night, Jesus prays, these things I have spoken to you that my joy may be in you, and that your joy may be complete. And I have come to understand why family is the road into that fullness, why it is not one path among many but the one most fitted to the shape of the promise. Consider who is praying. Christ does not come to us as a lone figure dropped out of the sky. He comes out of a family older than the world, the eternal communion of Father and Son, the love between them so total and so alive that theologians dared to call it a third person. Before there was anything, there was a family. The deepest fact about reality is not a force or a law or a void. It is a household. It is begetting and being begotten, giving and receiving, a Father who is only a Father because there is a Son. So when Jesus speaks of joy made complete, he is not pointing away from family toward something higher. He is pointing toward the very thing he came from, the life he has known from eternity and came to share. His joy is the joy of belonging utterly to a Father and pouring himself out for those he loves. When you marry, when you bring a child into the world, when you wear yourself down in the small unseen labors of a home, you are not stepping outside that divine life. You are stepping into a small image of it. Your family is a created echo of an uncreated one. The love you give your child rhymes with the love the Father has for the Son. The exhaustion, the tenderness, the way a parent would tear the sky open to protect a sleeping infant, all of it is the heavens pressed faintly into flesh, the eternal household leaving its fingerprint on yours. That is why the joy is not merely added to family but completed in it. We were made in the image of a God who is, at his very root, relation and gift and generation. To found a family is to do the most Godlike thing a creature can do, to participate from below in the begetting that God does from all eternity. Your home becomes a window. Through it, dimly and imperfectly, you glimpse the country you came from and are going to. And now a word for the young people reading this, the ones who do not yet have children. I want to tell you what it is like from where I stand. When I am out somewhere, a restaurant, anywhere, and a large family comes through the door, the noise and the chaos and the small bodies of them, something happens in me on two levels at once. The first is joy. A pure gladness at the sight, the way you feel watching something good and alive. But underneath it, almost in the same instant, a sadness reaches up and takes hold of my heart. Because I know now, at my age, after my own years of waiting, that I will never have that. I will never know the particular fruit of a family that large, the fullness of that table, the weight of all those lives gathered under one roof. The door to it has quietly closed, and I felt it close. And I am telling you plainly, because I love you and have no reason to lie to you: you will feel this too. You will. The day will come when you see what you passed up, and you will recognize the ache for what it is, and it will be too late to answer it. So please, learn from a man who got it wrong. Let my regret be worth something by becoming your wisdom. Do not wait yourself into a grief you cannot undo. Choose now, while the door is open, so that you may step into a joy that does not end.

Kirk Rollins

77,958 görüntüleme • 2 ay önce

An MIT professor solved the equation Wall Street pays $500K for, in a lecture about how to find the top of a hill. MIT put the whole thing online. it has been free for years. almost nobody finishes it. his point: finding the best possible answer to almost anything is one move. write down what you want to grow, take the derivative, and find the exact spot where it stops climbing. that spot is the answer. he is Denis Auroux, and his 18.02 lectures have taught more people calculus than most universities have students. now the equation from the post above, the one that tells you exactly how much to bet. it is not a secret formula. it is this. the growth of your money is a curve. bet too little and you are low on the hill. bet too much and you have gone over the top and started falling. Kelly's number is just the peak. no magic. no fund. one hill, and the single point where it stops going up. a quant I know rewatches this exact lecture before he sizes a single position. you were handed the formula and told to trust it. Auroux shows you where it actually comes from, for free, and it has been sitting there the whole time.

An MIT professor solved the equation Wall Street pays $500K for, in a lecture about how to find the top of a hill. MIT put the whole thing online. it has been free for years. almost nobody finishes it. his point: finding the best possible answer to almost anything is one move. write down what you want to grow, take the derivative, and find the exact spot where it stops climbing. that spot is the answer. he is Denis Auroux, and his 18.02 lectures have taught more people calculus than most universities have students. now the equation from the post above, the one that tells you exactly how much to bet. it is not a secret formula. it is this. the growth of your money is a curve. bet too little and you are low on the hill. bet too much and you have gone over the top and started falling. Kelly's number is just the peak. no magic. no fund. one hill, and the single point where it stops going up. a quant I know rewatches this exact lecture before he sizes a single position. you were handed the formula and told to trust it. Auroux shows you where it actually comes from, for free, and it has been sitting there the whole time.

Loran

94,834 görüntüleme • 11 gün önce

I need you to sit down for a moment and fully understand this: THE COUNTRY THAT SOLVES AI AND ROBOTICS WILL RULE THE WORLD AND SPACE. The west really only has Elon Musk, the east has 100s of companies fortified by an ENTIRE COUNTRY. Now some will argue no this is not true. No US company has the scale to MANUFACTURE, the compute power, and the finances to compete. Just a few hours ago we saw IRON for the first time, now you will. IRON, a 5’10, 150-lb AI humanoid robots are already building EV cars on the XPENG Motors factory floor. It has over 60 joints, a human-like spine, facial expressions, and male/female customizations The gait of this robot is the most human-like ever seen. Mass rollout in 2026. It is a very big deal. Because as the west does the best in clubbing each other over its head the last decade, China has looked and laughed and built at scale with a fortified government that has little diversion of goal, a 1000 year plan. The west has quietly plans and layers of lawyers and politicians. This is about where YOU LIVE and how you want to live. So when we kick the one person that is Atlas carrying our chance, in the groin, you make a choice on who’s world view you want. It is that simple. No, it is that simple. It ain’t no iPhone it is: whose’s world view will sustain. I can say no one is ready for what I have seen that is up for the next few years. You will think my bombastics were too tame.

I need you to sit down for a moment and fully understand this: THE COUNTRY THAT SOLVES AI AND ROBOTICS WILL RULE THE WORLD AND SPACE. The west really only has Elon Musk, the east has 100s of companies fortified by an ENTIRE COUNTRY. Now some will argue no this is not true. No US company has the scale to MANUFACTURE, the compute power, and the finances to compete. Just a few hours ago we saw IRON for the first time, now you will. IRON, a 5’10, 150-lb AI humanoid robots are already building EV cars on the XPENG Motors factory floor. It has over 60 joints, a human-like spine, facial expressions, and male/female customizations The gait of this robot is the most human-like ever seen. Mass rollout in 2026. It is a very big deal. Because as the west does the best in clubbing each other over its head the last decade, China has looked and laughed and built at scale with a fortified government that has little diversion of goal, a 1000 year plan. The west has quietly plans and layers of lawyers and politicians. This is about where YOU LIVE and how you want to live. So when we kick the one person that is Atlas carrying our chance, in the groin, you make a choice on who’s world view you want. It is that simple. No, it is that simple. It ain’t no iPhone it is: whose’s world view will sustain. I can say no one is ready for what I have seen that is up for the next few years. You will think my bombastics were too tame.

Brian Roemmele

446,773 görüntüleme • 9 ay önce

An MIT professor explained the one idea funds pay $500K for, and he does it in the first hour of freshman calculus. MIT put the whole lecture online. it has been free for twenty years. almost nobody finishes it. his point: calculus is not a hundred formulas to memorize. it is one idea. take two points on a curve, slide them together until the gap vanishes, and the slope you are left with is the derivative. everything else is just consequences. he is David Jerison, and his 18.01 lectures have taught more people calculus than any room on earth. skip to the board, where the power rule, the product rule, the chain rule, the fifty things you were forced to memorize, all fall out of that one limit. no formula sheet. no tricks. one definition, reused. that same slope is velocity. it is marginal cost. it is the gradient that trains a neural network. one operation, hiding everywhere something moves. the math is free. what nobody can sell you is the patience to understand the one limit instead of cramming the fifty formulas that fall out of it. that hour is the foundation, and it is the only part that ever pays.

An MIT professor explained the one idea funds pay $500K for, and he does it in the first hour of freshman calculus. MIT put the whole lecture online. it has been free for twenty years. almost nobody finishes it. his point: calculus is not a hundred formulas to memorize. it is one idea. take two points on a curve, slide them together until the gap vanishes, and the slope you are left with is the derivative. everything else is just consequences. he is David Jerison, and his 18.01 lectures have taught more people calculus than any room on earth. skip to the board, where the power rule, the product rule, the chain rule, the fifty things you were forced to memorize, all fall out of that one limit. no formula sheet. no tricks. one definition, reused. that same slope is velocity. it is marginal cost. it is the gradient that trains a neural network. one operation, hiding everywhere something moves. the math is free. what nobody can sell you is the patience to understand the one limit instead of cramming the fifty formulas that fall out of it. that hour is the foundation, and it is the only part that ever pays.

Loran

1,068,723 görüntüleme • 12 gün önce

IN A 1997 KEYNOTE A DEVELOPER TOLD A ROOM FULL OF PROGRAMMERS THAT THE COMPUTER REVOLUTION HAD NOT ACTUALLY HAPPENED YET. THEN HE PLAYED A CLIP OF WINDOWS, ICONS AND LIVE EDITING RUNNING ON A MACHINE FROM 1973 AND THE ROOM WENT QUIET. 62 minutes from Alan Kay -- the man who invented the word "object-oriented" and helped build the first modern personal computer at Xerox PARC. -> The idea that lands: almost everything you call "computing" is just paper, digitized. Documents, mail, folders. We took the most powerful medium ever made and used it to imitate the office. The real machine -- the one that thinks with you, that you shape live instead of typing at -- was sketched in the 60s and 70s, then quietly abandoned. He calls modern software an Egyptian pyramid: millions of bricks stacked by brute force, no structure underneath. And now AI is quietly hauling us back toward what he wanted -- you describe intent, the machine builds the how. Not a revolution from nowhere. A return to a dream we walked away from. You thought this was the future. This is the talk that shows you it is a detour we have been on for 40 years. Save this. It reframes the whole industry ↓

IN A 1997 KEYNOTE A DEVELOPER TOLD A ROOM FULL OF PROGRAMMERS THAT THE COMPUTER REVOLUTION HAD NOT ACTUALLY HAPPENED YET. THEN HE PLAYED A CLIP OF WINDOWS, ICONS AND LIVE EDITING RUNNING ON A MACHINE FROM 1973 AND THE ROOM WENT QUIET. 62 minutes from Alan Kay -- the man who invented the word "object-oriented" and helped build the first modern personal computer at Xerox PARC. -> The idea that lands: almost everything you call "computing" is just paper, digitized. Documents, mail, folders. We took the most powerful medium ever made and used it to imitate the office. The real machine -- the one that thinks with you, that you shape live instead of typing at -- was sketched in the 60s and 70s, then quietly abandoned. He calls modern software an Egyptian pyramid: millions of bricks stacked by brute force, no structure underneath. And now AI is quietly hauling us back toward what he wanted -- you describe intent, the machine builds the how. Not a revolution from nowhere. A return to a dream we walked away from. You thought this was the future. This is the talk that shows you it is a detour we have been on for 40 years. Save this. It reframes the whole industry ↓

slash1s

294,020 görüntüleme • 1 ay önce