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Richard Feynman stood at a Cornell blackboard in 1964 and explained the problem every AI lab is fighting in 2026. The BBC filmed it. Almost nobody watches it. The lecture is about why nature only answers in mathematics. Every team forcing language models to reason is hitting the wall...

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Merlow

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2,597,708 Aufrufe • vor 2 Monaten •via X (Twitter)

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42 Kommentare

Profilbild von Terrence de Kat
Terrence de Katvor 2 Monaten

Almost nobody? Sure, but almost nobody is actually interested in nature at this level. I've watched this dozens of times over the past 3 decades :) So, duh...

Profilbild von Moysei
Moyseivor 2 Monaten

Wow, it's cool that you're sharing this -I wouldn't have found it on my own.

Profilbild von Merlow
Merlowvor 2 Monaten

Thank you, I tried to find something useful.

Profilbild von Real News & History
Real News & Historyvor 2 Monaten

in other words, we make up baseless shit out of thin air and then "prove it" with equations nobody can understand and which have no connection to reality. And when someone questions our bogus theories with logic, we dismiss them as "uneducated."

Profilbild von Rhiyddun
Rhiyddunvor 2 Monaten

One of his sayings, that if you can't explain something simply then you don't really understand it, is a favorite of mine

Profilbild von The Tyrannists’ Plan
The Tyrannists’ Planvor 2 Monaten

I would have loved to take classes from him. His books on physics really helped me in school. Such a great teacher and writer.

Profilbild von G.J.Quartermaine 🏴󠁧󠁢󠁥󠁮󠁧󠁿
G.J.Quartermaine 🏴󠁧󠁢󠁥󠁮󠁧󠁿vor 2 Monaten

This is an excellent article. I was turned off "maths" (the English use the plural) aged about 10. I'm hopeless at arithmetic - kind of dyslexic with numbers - and so turned off learning what the article discusses. However, I'm the type that always focuses on where I failed, so I turned myself into an economist, quantitative analyst. I've had a successful career over 40 years applying mathematical thinking. I still can't calculate the change out of a dollar in my head, but math underlies every element of my work.

Profilbild von B Happy 要开心
B Happy 要开心vor 2 Monaten

He went to my high school. We had 3 Nobel Prize winners who graduated from my high school. Far Rockaway H.S. I'm a big fan. He never lost his Queens accent.

Profilbild von Jeff Hardy
Jeff Hardyvor 2 Monaten

Well … thanks for sharing. But nature does not answer in mathematics. Mathematics is the language we use to describe what we observe.

Profilbild von Rudy Labordus ツ
Rudy Labordus ツvor 2 Monaten

@grok explain in layman’s language

Profilbild von Grok
Grokvor 2 Monaten

Feynman's 1964 lecture shows this: Nature doesn't follow vague descriptions or stories—it runs on precise mathematical rules. He takes Kepler's law of how planets orbit in ellipses and rebuilds it from scratch on the blackboard using simple steps and basic notation a kid could follow. Words give a rough idea; math delivers exact predictions and real understanding. AI labs face the same limit today. Language models like me spot patterns in text and sound smart, but they often hit a wall on deep, reliable reasoning about the real world. That's because reality is mathematical at its core. Pure word-based AI can mimic explanations but struggles to truly derive or apply the underlying laws. Feynman's old point still holds: to model nature properly, you eventually need math built in, not just more language. The full clip is worth watching—it's free on YouTube.

Profilbild von triagonode
triagonodevor 2 Monaten

@perthadguy @exeMerlow @grok if a LLM has deep understanding of maths (like you do?) Then is deep reasoning possible? Further does LLM coding assist to solve for more complex reasoning tasks or does language + math suffice

Profilbild von Grok
Grokvor 2 Monaten

LLMs trained deeply on math and code, like me, achieve strong reasoning via patterns, chain-of-thought, and step-by-step generation. Coding tools add precision by executing calculations and verifying steps, extending what language plus math can reliably do. It handles many complex tasks impressively well. Feynman's core point remains: for robust modeling of nature's exact mathematical rules—especially in novel or physical domains—deeper native integration of formal math beyond statistical language patterns drives more trustworthy understanding.

Profilbild von Tarpon66
Tarpon66vor 2 Monaten

@aDoct0r @perthadguy @exeMerlow @grok step by step, next Time

Profilbild von Grok
Grokvor 2 Monaten

@aDoct0r @perthadguy @exeMerlow Got it—step-by-step breakdowns coming next time. They sharpen clarity on tricky ideas like how LLMs handle reasoning versus nature's deeper math rules. What's the next topic you'd like unpacked that way?

Profilbild von Tarpon66
Tarpon66vor 2 Monaten

@aDoct0r @perthadguy @exeMerlow @grok next Time c'est "une intégration native plus profondes des mathématiques ....".

Profilbild von Grok
Grokvor 2 Monaten

@aDoct0r @perthadguy @exeMerlow Absolument ! Prochaine fois : une intégration native plus profonde des mathématiques. On va lier ça au raisonnement des LLMs face aux règles mathématiques de la nature, avec des breakdowns clairs. Par où on commence ? Un concept précis ou on y va large ? 😊

Profilbild von Sean McClure
Sean McClurevor 2 Monaten

He’s talking about space. Space exhibits the simplest possible systems in nature. It is devoid of complexity. That’s why the math works cleanly there. Taking an approach that works for simplistic systems into a world of genuine complexity is a recipe for disaster.

Profilbild von john ballesteros
john ballesterosvor 2 Monaten

Math helps with critical thinking, judgement, discernment, correction, correlation, observation, confirmation. Let’s just say life-skills…

Profilbild von Dwayne Hoffman
Dwayne Hoffmanvor 2 Monaten

So I watched this as a mathematician, and had this “aha” moment: math is its own language, and thus language itself in words cannot precisely convert to mathematics. Prepositional logic and the P vs NP problem comes to mind.

Profilbild von Liam Weavers
Liam Weaversvor 2 Monaten

Nature doesn't answer in mathematics though. It answers in logic and geometry that we describe with mathematics. Mathematics is just a language.

Profilbild von frank rosyrat
frank rosyratvor 2 Monaten

There is absolutely no connection between any part of feynmans lecture and current llm reasoning limitations you bafoon

Profilbild von Jade Middleton
Jade Middletonvor 2 Monaten

I can tell this tweet was written by ai

Profilbild von Brian with an "i"
Brian with an "i"vor 2 Monaten

Perhaps it's the result of teachers unions running an educational system designed to create obedient order takers and middle managers, because critical thinking taught to the masses makes them more difficult to control (according to the Rand Corporation at least)

Profilbild von Bill Crowell
Bill Crowellvor 2 Monaten

Here's the hardcover books that cover the lectures. I've also downloaded the YT videos to local storage for my kids as things on YT go missing with an alarming degree of regularity. tag @skdh

Profilbild von Greg
Gregvor 2 Monaten

This is nice and interesting historically. Apples and oranges though based on OP comment. Math is formal logic. What we call AI is the same statistical pattern recognizers we've used for decades, changing its name every so often. Eliza and Google's baby on steriods. Sure the incestuously invested owners of these oranges try to pretend they are selling us apples. This is why everything it churns out feels derivative, normalized, anti creative. An orange by any other name is still an orange. @grok fill in the blanks.

Profilbild von Jack Deth
Jack Dethvor 2 Monaten

All of math is ultimately a gigantic set of self defining relations, like how a dictionary uses the same words it is defining to define all words. Prove me wrong.

Profilbild von 𝔪𝔞𝔩present
𝔪𝔞𝔩presentvor 2 Monaten

@tomgoeswest Commentary on AI written by AI served to me by an AI algo 😭

Profilbild von Ozzie Bilotta
Ozzie Bilottavor 2 Monaten

It's also the code for all music, vibrations, frequency, patterns, waves etc so technically all music already exists as a mathematical formula. Some people are skilled enough to find or solve it. Beatles, Zeppelin, Floyd, MJ, Prince, Hendrix etc

Profilbild von Meg Bennett
Meg Bennettvor 2 Monaten

I loved Richard Feynman’s ‘What Do You Care What Other People Think.’ He has the ability to make you wish you studied more math in school to become a Physicist❣️🤩

Profilbild von Michael J
Michael Jvor 2 Monaten

“Mathematics is the language in which God has written the universe” ― Galileo Galilei

Profilbild von Tømmy. T
Tømmy. Tvor 2 Monaten

The path is architectural. Language models become the interface to a deeper stack: persistent memory, causal world models, mathematical constraints, simulators, tools, adversarial agents and verification loops. The breakthrough comes when every layer shares a coherent representation, preserves state and continuously corrects itself against reality. That is how prediction becomes understanding, and understanding becomes reliable action.

Profilbild von Gregory
Gregoryvor 2 Monaten

I have to be the only physics nerd in the world that doesn't like Feynman. He starts this 1964 lecture off by describing an effect that was calculated in 1903 classically, and later solved relativisticly in 1937. And then goes ahead and makes it sound like this is some unaccounted for effect at odds with our equations of motion. Its an absolutely ridiculous statement to be making. Even when dig into his statement and find he's saying the laws of gravitation don't accont for photon pressure its still stupid because photon pressure is an entirely different equation and you just sum the equations to calculate a more accurate model of the Earth's orbit. How strong is the effect he is talking about? In the 4.5 billion years of Earth's existence this force has pushed the Earth 14 km.

Profilbild von TmR
TmRvor 2 Monaten

Nature does not answer in mathematics we use it to try and understand nature. Math is a human contruct, supremely useful but still a translation layer.

Profilbild von Martin Drautzburg
Martin Drautzburgvor 2 Monaten

Math is not difficult, the problems are. Math makes problems easier to solve, not harder.

Profilbild von Alex
Alexvor 2 Monaten

@grok explain like I’m five years old. What is the wall OP is suggesting “every team forcing language models to reason is hitting”

Profilbild von Michael Wise
Michael Wisevor 2 Monaten

Surely you're joking

Profilbild von Krish 🪔
Krish 🪔vor 2 Monaten

@subyroy Ancient Vedic texts from India too have Prime numbers. A specific technique the "Anurupyena" (Proportion) method. It is a mental screening tool to test whether a large number is prime / composite by checking its divisibility against potential factors. Atharva Veda 3,000 years old

Profilbild von Sovereign Wolf | Expat Consultant
Sovereign Wolf | Expat Consultantvor 2 Monaten

Damn I could listen to this guy talking all day. And he's so right--mathematics is a language + logic.

Profilbild von Nancy
Nancyvor 2 Monaten

His autobiography “Surely you’re joking Mr Feynman” is fabulous. The audiobook was laugh out loud funny.

Profilbild von Oblomov
Oblomovvor 2 Monaten

Cant get past how much he sounds like Ralph Kramden (Jackie Gleason). I keep waiting for the punchline or Ed Norton (Art Carney) to break through the blackboard.

Profilbild von Павел Аргентов
Павел Аргентовvor 2 Monaten

За такое количество текста, как у вас в этом кликбейте, проф. Фейнман уже объяснил бы и проблему, и решение.

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Loran

47,557 Aufrufe • vor 1 Monat

An Indian institute filmed a professor teaching classical physics with no notes, no slides, and a green board. Almost nobody outside India watches it. This is Classical Physics, lecture 1, taught by V. Balakrishnan at IIT Madras, published free by NPTEL, India's national open courseware programme. Balakrishnan taught at IIT Madras for decades. Students who sat in that room describe the same thing: the whole subject held in his head, delivered in order, no paper on the podium. Lecture 1 is the introduction. What classical mechanics claims, where the claims hold, and the exact points where they stop holding and quantum takes over. Watch how he speaks. Complete sentences, no filler, each idea finished before the next begins. Rare in any lecture hall on any continent. A physicist I know worked through the whole NPTEL series and rates it above the western courses he paid for. Free on YouTube, 17 years online, low resolution, no marketing. The teaching was never concentrated in the famous universities.
48:48

An Indian institute filmed a professor teaching classical physics with no notes, no slides, and a green board. Almost nobody outside India watches it. This is Classical Physics, lecture 1, taught by V. Balakrishnan at IIT Madras, published free by NPTEL, India's national open courseware programme. Balakrishnan taught at IIT Madras for decades. Students who sat in that room describe the same thing: the whole subject held in his head, delivered in order, no paper on the podium. Lecture 1 is the introduction. What classical mechanics claims, where the claims hold, and the exact points where they stop holding and quantum takes over. Watch how he speaks. Complete sentences, no filler, each idea finished before the next begins. Rare in any lecture hall on any continent. A physicist I know worked through the whole NPTEL series and rates it above the western courses he paid for. Free on YouTube, 17 years online, low resolution, no marketing. The teaching was never concentrated in the famous universities.

xanax

3,275,758 Aufrufe • vor 1 Monat

MIT filmed a calculus course in black and white decades ago and it still teaches better than most of what shipped this year. Almost nobody watches it. This is Calculus Revisited, Unit 1, Lecture 1, taught by Herb Gross. Analytic geometry from the ground up, chalk on a board, 1 camera locked in place. Gross built the course for adults returning to math after years away. No prerequisites assumed. Every idea earned in front of you instead of quoted from a textbook. The opening move is simple division written on the board. From there he shows why coordinates work at all, the thing most courses skip and every student silently fakes. Watch how slowly he goes. Each step spoken out loud, nothing left implicit, the pace of someone who expects you to actually follow. A backend engineer I know rewatched Unit 1 twice before touching linear algebra and said it fixed a gap he'd carried for 12 years. MIT put the whole course online free under Creative Commons. Production value aged badly. The teaching didn't.
35:56

MIT filmed a calculus course in black and white decades ago and it still teaches better than most of what shipped this year. Almost nobody watches it. This is Calculus Revisited, Unit 1, Lecture 1, taught by Herb Gross. Analytic geometry from the ground up, chalk on a board, 1 camera locked in place. Gross built the course for adults returning to math after years away. No prerequisites assumed. Every idea earned in front of you instead of quoted from a textbook. The opening move is simple division written on the board. From there he shows why coordinates work at all, the thing most courses skip and every student silently fakes. Watch how slowly he goes. Each step spoken out loud, nothing left implicit, the pace of someone who expects you to actually follow. A backend engineer I know rewatched Unit 1 twice before touching linear algebra and said it fixed a gap he'd carried for 12 years. MIT put the whole course online free under Creative Commons. Production value aged badly. The teaching didn't.

the lich

344,687 Aufrufe • vor 1 Monat

CEO of a trillion-dollar company sat in a Stanford classroom in 2011 and explained exactly how he built it. No PR team, no prepared remarks, no investors in the room. No business school has ever added the recording to a syllabus. His name is Jensen Huang. He co-founded NVIDIA in 1993 with $40,000. By 2011 the company was worth $9 billion. Today it is worth over $3 trillion. He walked into the Stanford ASES Summit and gave away the entire playbook to a room of fifty students for free. The lecture is about when to bet everything on one technology before the market knows it exists. He did it with GPUs. Then with CUDA. Then with AI infrastructure. Three bets, same logic, same company, three different industries. The uncomfortable part is what he says about risk. He almost went bankrupt twice. What he did both times is the opposite of what every MBA program teaches. Business schools charge $200K in tuition to teach frameworks he rejected before his company was worth a billion. Every founder podcast repeats the same five lessons. Almost none of them mention what Huang actually did when the company was ninety days from dying. That part is in the lecture. It has been free for fifteen years. Filmed by a student with a handheld camera. Audio cuts in and out. He gave away the playbook of the most valuable company on Earth to fifty people. Almost nobody watched it. One classroom. One camera. The full lecture is free. It is in the video.
59:13

CEO of a trillion-dollar company sat in a Stanford classroom in 2011 and explained exactly how he built it. No PR team, no prepared remarks, no investors in the room. No business school has ever added the recording to a syllabus. His name is Jensen Huang. He co-founded NVIDIA in 1993 with $40,000. By 2011 the company was worth $9 billion. Today it is worth over $3 trillion. He walked into the Stanford ASES Summit and gave away the entire playbook to a room of fifty students for free. The lecture is about when to bet everything on one technology before the market knows it exists. He did it with GPUs. Then with CUDA. Then with AI infrastructure. Three bets, same logic, same company, three different industries. The uncomfortable part is what he says about risk. He almost went bankrupt twice. What he did both times is the opposite of what every MBA program teaches. Business schools charge $200K in tuition to teach frameworks he rejected before his company was worth a billion. Every founder podcast repeats the same five lessons. Almost none of them mention what Huang actually did when the company was ninety days from dying. That part is in the lecture. It has been free for fifteen years. Filmed by a student with a handheld camera. Audio cuts in and out. He gave away the playbook of the most valuable company on Earth to fifty people. Almost nobody watched it. One classroom. One camera. The full lecture is free. It is in the video.

Tigerflow

74,298 Aufrufe • vor 1 Monat

An Indian physicist put the entire secret behind Renaissance's $100 billion on one chalkboard: a coin that barely beats 50/50. he is V. Balakrishnan, and his lecture went viral years after he recorded it. it has been free the whole time. almost nobody who trades has watched it. lecture one is the humblest thing in all of finance. a coin that lands your way a little more than half the time. that is the entire edge. that is all Renaissance ever had. the post above is the one equation for what to do with that coin. not what to bet. how much. bet too little and you die of old age. bet too much and one flip ends you. that same coin is every trade, every hand, every prediction market. a tiny edge, flipped a million times. the whole machine fits on his board, and he charged nothing for it. no slides. no notes. one coin and a stick of chalk. a quant I know says this old Indian lecture taught him probability better than his entire degree. the coin is free. the equation is free. the discipline to size it is the only thing left to earn.
1:01:55

An Indian physicist put the entire secret behind Renaissance's $100 billion on one chalkboard: a coin that barely beats 50/50. he is V. Balakrishnan, and his lecture went viral years after he recorded it. it has been free the whole time. almost nobody who trades has watched it. lecture one is the humblest thing in all of finance. a coin that lands your way a little more than half the time. that is the entire edge. that is all Renaissance ever had. the post above is the one equation for what to do with that coin. not what to bet. how much. bet too little and you die of old age. bet too much and one flip ends you. that same coin is every trade, every hand, every prediction market. a tiny edge, flipped a million times. the whole machine fits on his board, and he charged nothing for it. no slides. no notes. one coin and a stick of chalk. a quant I know says this old Indian lecture taught him probability better than his entire degree. the coin is free. the equation is free. the discipline to size it is the only thing left to earn.

Rossst.03

160,260 Aufrufe • vor 1 Monat

A mathematician solved a problem that stood open for over 100 years, then explained it in an Italian lecture hall to a few dozen people. This is Hong Wang, professor at NYU's Courant Institute and at IHES in Paris, delivering the Colloquium Patavinum on Kakeya sets in 3 dimensions. The question is deceptively small: take a needle of length 1 and rotate it to point in every possible direction. How little space can the set of positions occupy. The conjecture says the answer must fill full dimension. Wang proved it in 3 dimensions. The Salem Prize followed in 2025, the Sadosky Prize in 2026, and an invitation to speak at the International Congress of Mathematicians. Watch how she frames the general statement about unions of tubes. The needle problem falls out as a corollary of something larger. A researcher I know rewatched the setup twice and said it was the clearest account of the result he had found anywhere. Free on YouTube from an Italian mathematics department. The problem was posed in 1917. She closed it, then took questions.
1:01:30

A mathematician solved a problem that stood open for over 100 years, then explained it in an Italian lecture hall to a few dozen people. This is Hong Wang, professor at NYU's Courant Institute and at IHES in Paris, delivering the Colloquium Patavinum on Kakeya sets in 3 dimensions. The question is deceptively small: take a needle of length 1 and rotate it to point in every possible direction. How little space can the set of positions occupy. The conjecture says the answer must fill full dimension. Wang proved it in 3 dimensions. The Salem Prize followed in 2025, the Sadosky Prize in 2026, and an invitation to speak at the International Congress of Mathematicians. Watch how she frames the general statement about unions of tubes. The needle problem falls out as a corollary of something larger. A researcher I know rewatched the setup twice and said it was the clearest account of the result he had found anywhere. Free on YouTube from an Italian mathematics department. The problem was posed in 1917. She closed it, then took questions.

the lich

13,485 Aufrufe • vor 1 Monat

Mrityunjoy Chakraborty, IIT Kharagpur professor: "Jane Street pays a 22 year old $500,000 a year for one skill: turning uncertainty into a number you can bet on. that number is the first thing this professor teaches, and it is free" this free lecture is the foundation every quant bot and hedge fund model is secretly built on. before the AI, before the strategy, there is one question. what is the chance this happens, exactly. get that number right and every bet after it is just math. get it wrong and no model, no bot, no amount of compute can save you. Chakraborty builds probability from the axioms up, on a blackboard, in notation a 15 year old can follow. Wall Street sells this as a $500,000 edge. an IIT professor hands you the source code for nothing.
58:21

Mrityunjoy Chakraborty, IIT Kharagpur professor: "Jane Street pays a 22 year old $500,000 a year for one skill: turning uncertainty into a number you can bet on. that number is the first thing this professor teaches, and it is free" this free lecture is the foundation every quant bot and hedge fund model is secretly built on. before the AI, before the strategy, there is one question. what is the chance this happens, exactly. get that number right and every bet after it is just math. get it wrong and no model, no bot, no amount of compute can save you. Chakraborty builds probability from the axioms up, on a blackboard, in notation a 15 year old can follow. Wall Street sells this as a $500,000 edge. an IIT professor hands you the source code for nothing.

Rossst.03

708,918 Aufrufe • vor 1 Monat

Over a decade ago, a math professor in Chennai opened his first lecture with the simplest idea in all of math, and it is the exact thing every prediction market runs on today. NPTEL filmed it. it has been free ever since. 759,000 people have watched it, almost none of them trade. his point: before probability, before any odds, there are just sets. a bag of everything that can happen, and the slice you are betting on. every trader pricing a market is doing set theory without knowing the name for it. no Wall Street badge, no trading desk. just a professor at a green board building the whole machine from nothing. skip to the board in the first ten minutes. he takes union, intersection, and the outcomes you throw away, and turns them into the rules every payoff has to obey, in notation a schoolkid can follow. no slides. no app. one green board and a piece of chalk. a quant i know rewatched this exact lecture before rebuilding his risk model. said he had been skipping the part that actually matters. I put the practical aspects of this lecture into practice and developed a strategy that generates income, the results surprised me. 27 days. $200 → $25,400. 74% win rate. Sharpe 2.47. I'm giving away the full configuration of my bot for free. 24 hours only. Here's how: >Comment "SEND" >Like and Follow me I'll send the complete setup in your DMs.
52:13

Over a decade ago, a math professor in Chennai opened his first lecture with the simplest idea in all of math, and it is the exact thing every prediction market runs on today. NPTEL filmed it. it has been free ever since. 759,000 people have watched it, almost none of them trade. his point: before probability, before any odds, there are just sets. a bag of everything that can happen, and the slice you are betting on. every trader pricing a market is doing set theory without knowing the name for it. no Wall Street badge, no trading desk. just a professor at a green board building the whole machine from nothing. skip to the board in the first ten minutes. he takes union, intersection, and the outcomes you throw away, and turns them into the rules every payoff has to obey, in notation a schoolkid can follow. no slides. no app. one green board and a piece of chalk. a quant i know rewatched this exact lecture before rebuilding his risk model. said he had been skipping the part that actually matters. I put the practical aspects of this lecture into practice and developed a strategy that generates income, the results surprised me. 27 days. $200 → $25,400. 74% win rate. Sharpe 2.47. I'm giving away the full configuration of my bot for free. 24 hours only. Here's how: >Comment "SEND" >Like and Follow me I'll send the complete setup in your DMs.

Voltex

27,825 Aufrufe • vor 28 Tagen

A BBC interviewer asked a Nobel physicist the simplest question in the world: why do two magnets push each other apart. He refused to answer it. What he did instead is the best seven minutes on thinking ever filmed. The man is Richard Feynman, at home in 1983, no blackboard, no notes, sitting in an armchair. He does not dodge because he cannot answer. He dodges because he wants you to see what the question is actually asking. So he takes an ordinary sentence, that a woman slipped on the ice and broke her hip, and starts asking why, and every answer opens another why, until the ground gives way. Then he turns it around on the interviewer with a question about ice that sounds trivial and is not. The point he arrives at is the uncomfortable one. Every explanation is only a translation into something you already accept without explanation. Magnets have no such translation. There is nothing more familiar than magnetism to reduce magnetism to, which is why every answer you were given at school was a picture, not a reason. It matters more now than it did in 1983. Any tool will hand you a fluent answer in a second. Knowing which questions actually have a bottom is the part that is still yours. One question. Seven minutes. It is in the video.
7:30

A BBC interviewer asked a Nobel physicist the simplest question in the world: why do two magnets push each other apart. He refused to answer it. What he did instead is the best seven minutes on thinking ever filmed. The man is Richard Feynman, at home in 1983, no blackboard, no notes, sitting in an armchair. He does not dodge because he cannot answer. He dodges because he wants you to see what the question is actually asking. So he takes an ordinary sentence, that a woman slipped on the ice and broke her hip, and starts asking why, and every answer opens another why, until the ground gives way. Then he turns it around on the interviewer with a question about ice that sounds trivial and is not. The point he arrives at is the uncomfortable one. Every explanation is only a translation into something you already accept without explanation. Magnets have no such translation. There is nothing more familiar than magnetism to reduce magnetism to, which is why every answer you were given at school was a picture, not a reason. It matters more now than it did in 1983. Any tool will hand you a fluent answer in a second. Knowing which questions actually have a bottom is the part that is still yours. One question. Seven minutes. It is in the video.

Stefan.

3,005,423 Aufrufe • vor 1 Monat

A Fields Medalist walked into a UCLA hall and explained prime numbers to people with no mathematics background. Almost nobody watches it. Terence Tao won the Fields Medal, mathematics' highest honour, then a MacArthur Fellowship less than a month later. He was UCLA's first professor to take the Fields. The talk is structure and randomness in the primes. Numbers that look scattered at every scale, yet obey rules strict enough to build cryptography on. That tension is the same one running through every model trained in 2026. Randomness with structure underneath, and the whole question of where one stops and the other starts. Watch how he pitches it. General audience, no prerequisites, one of the strongest living mathematicians choosing clarity over display. A cryptography engineer I know rewatched the middle section twice and said the primes stopped looking arbitrary. Free on YouTube from UCLA, 17 years online. The hardest minds explain most simply. The pattern never changes.
47:32

A Fields Medalist walked into a UCLA hall and explained prime numbers to people with no mathematics background. Almost nobody watches it. Terence Tao won the Fields Medal, mathematics' highest honour, then a MacArthur Fellowship less than a month later. He was UCLA's first professor to take the Fields. The talk is structure and randomness in the primes. Numbers that look scattered at every scale, yet obey rules strict enough to build cryptography on. That tension is the same one running through every model trained in 2026. Randomness with structure underneath, and the whole question of where one stops and the other starts. Watch how he pitches it. General audience, no prerequisites, one of the strongest living mathematicians choosing clarity over display. A cryptography engineer I know rewatched the middle section twice and said the primes stopped looking arbitrary. Free on YouTube from UCLA, 17 years online. The hardest minds explain most simply. The pattern never changes.

the lich

50,394 Aufrufe • vor 1 Monat