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A DEVELOPER WALKED ON STAGE DRESSED AS A 1973 ENGINEER AND "PREDICTED" THE FUTURE OF PROGRAMMING. THE TWIST: EVERYTHING HE DESCRIBED WAS ALREADY INVENTED 40 YEARS EARLIER AND WE STILL REFUSE TO USE IT. 32 minutes from Bret Victor, doing the most quietly savage talk on our entire industry.... -> The idea that lands: we write code as step-by-step text instructions and call that "Just how programming is". He shows four better ways -- all discovered in the 60s and 70s, all abandoned. Manipulate the data directly instead of typing blind code. Tell the machine your goal instead of every tiny step. We saw all this, then walked away. Why? The moment you're sure you know what programming is, you stop seeing anything better. That certainty is the cage. And now AI is dragging us back to exactly what he begged for -- you describe the goal in plain words, the machine works out the how. The future he mourned is arriving anyway. You thought text files were just how code works. This is the talk that shows it was a choice, and maybe the wrong one. Watch this one. It'll ruin how you see your job ↓show more

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678,451 次观看 • 6 天前 •via X (Twitter)

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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

290,354 次观看 • 5 天前

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 ↓

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IN 1982 GRACE HOPPER WALKED INTO THE NSA AND EXPLAINED THE NEXT 40 YEARS OF COMPUTING 48 minutes from the woman who invented the compiler -- the first person who made a machine understand human words. -> The idea that lands: stop bending humans to the machine. Bend the machine to humans. She built the first compiler when the experts swore computers could only crunch numbers. She wanted you to write in plain words and let the machine handle the translation. Forty years later you barely write code at all -- you tell the model what you want in plain English and it writes it for you. The compiler was step one. The LLM is the same idea, finished. Memorizing syntax was never the skill -- saying clearly what you actually want is. This is where that idea was born. Most people think talking to your computer in plain English started in 2023. The ones who watch this know a Navy admiral called it in 1982. Bookmark & Watch it today ↓

IN 1982 GRACE HOPPER WALKED INTO THE NSA AND EXPLAINED THE NEXT 40 YEARS OF COMPUTING 48 minutes from the woman who invented the compiler -- the first person who made a machine understand human words. -> The idea that lands: stop bending humans to the machine. Bend the machine to humans. She built the first compiler when the experts swore computers could only crunch numbers. She wanted you to write in plain words and let the machine handle the translation. Forty years later you barely write code at all -- you tell the model what you want in plain English and it writes it for you. The compiler was step one. The LLM is the same idea, finished. Memorizing syntax was never the skill -- saying clearly what you actually want is. This is where that idea was born. Most people think talking to your computer in plain English started in 2023. The ones who watch this know a Navy admiral called it in 1982. Bookmark & Watch it today ↓

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Larry Ellison just told every software engineer on Earth their job description is dead. Not evolving. Dead. Ellison: “The code that Oracle is writing, Oracle isn’t writing. Our AI models are writing.” This is not a startup demo. This is one of the largest infrastructure monopolies on the planet telling you it already replaced the people who built it. For fifty years, building software meant translating human intent into machine instructions. Line by line. Bug by bug. Sprint by sprint. That entire layer is gone. Ellison: “We don’t write the procedure. We declare our intent.” That sentence just made the entire engineering labor market flinch. The procedure was the job. The procedure was the paycheck. The procedure was what made a developer valuable. And now the machine does it without being asked twice. Ellison: “We just tell the model what we want the program to do, and then the AI comes up with a step-by-step process to actually do it.” You are no longer paid to build. You are paid to think. And most organizations have no idea how to evaluate that. The companies still hiring armies of developers to grind through codebases are paying salaries the machine already made worthless. Not in years. In seconds. When a company worth hundreds of billions hands the keyboard to the machine and tells you the output is better, the debate is not winding down. The debate is over. The enterprise that wins this decade does not write the best code. It removes the human from the process entirely and runs on intent alone. The programmers who survive are the ones who realize the craft is no longer typing. It is architecture. It is judgment. It is knowing what to build and why. Everything else now belongs to the machine. And the machine does not negotiate severance.

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Anthropic Claude Code engineer: "The moment you're reviewing every line Claude writes, you became its tester. You weren't hired for that." this 36 min talk is the clearest breakdown of how to get yourself out of the loop entirely the shift is simple: you stop prompting and start building agents that work instead of you agents that run, check themselves, and keep going while your laptop is closed watch it, then build your own with the step-by-step guide below

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ONE OF THE MINDS BEHIND JAVA GAVE A LECTURE WHERE HE BANNED HIMSELF FROM USING ANY BIG WORD UNTIL HE DEFINED IT FIRST AND IN DOING SO QUIETLY EXPLAINED HOW EVERY GREAT SYSTEM GETS BUILT A talk from Guy Steele -- co-author of the Java spec and a designer of Scheme -- where the form of the talk is the lesson. -> The moment you catch what he's doing, it rewires you. He starts with only the smallest words, then builds every larger idea live, in front of you, from the pieces he already gave you. The talk grows its own vocabulary as it goes. That's the whole secret of language and system design he's smuggling in: you don't ship something huge and finished. You ship a small core and the means to grow it. Miss that and you spend your career fighting your own tools. Memorizing a language was never the skill -> understanding how a good one is meant to grow is. And as AI starts generating the primitives you build on, knowing what makes a foundation extensible instead of brittle is the entire game. Twenty-five years on, language designers still point to this talk as the cleanest demonstration of the idea ever performed. Bookmark it & Watch how he builds the whole thing from nothing ↓

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YOU BETTER STOP DOING EVERYTHING RIGHT NOW Y’all….. This is just worth your time and you better watch it twice!! Two for Tuesday!! This cat sees something in the sky that just looks all wrong… He begins to record and he tells you everything that is happening like a sports announcer… Watch this!!! This is what he captured…..

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A DEVELOPER PROVED THE REGEX YOU'VE WRITTEN A THOUSAND TIMES IS SECRETLY A COMPILER AND THAT ALMOST NO ONE WHO USES THEM HAS ANY IDEA WHAT ACTUALLY RUNS 36 minutes from Paul Wankadia, the engineer behind a regex engine that compiles your pattern straight down to raw machine code -- walking through what really happens between the slashes. -> The moment it clicks, regex stops being magic punctuation you paste from Stack Overflow and becomes what it actually is: a tiny machine. Your pattern gets turned into a state machine, and that machine is what runs against every character of your text. That one idea explains everything you never understood. Why one regex returns instantly and a nearly identical one hangs your whole server. Why some patterns are safe and others are a denial-of-service waiting to happen. It was never random -- it's whether the machine underneath is built well or badly. Writing a regex was never the skill -> reading one is. And now that an AI agent hands you dense, clever patterns you'd never write yourself, the person who can see the machine underneath is the one who catches the one that takes down production at 3am. Everyone copies regex and prays. This is the talk that ends the praying. Save it. The next time a pattern "Just works," you'll actually know why ↓

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IN 1999 MIT FILMED A MATH LECTURE THAT QUIETLY BECAME THE FOUNDATION OF EVERY AI MODEL YOU'VE EVER USED AND ALMOST NO ONE WAS TAUGHT TO SEE IT THAT WAY 39 minutes from Gilbert Strang, who taught this at MIT for over 60 years -- the linear algebra course an entire generation of engineers and data scientists grew up on. -> The shift it creates: you stop seeing matrices as boring grids of numbers and start seeing them as the language of space, data, and motion itself. School drilled you to crunch matrices by hand and never told you why. Strang shows you what they actually mean. Every neural net, every embedding, every model you prompt is linear algebra running underneath. The math you skipped is the engine of the thing you use all day. Memorizing the steps was never the skill -> seeing what the numbers do is. This is where it finally clicks. Most people fear linear algebra and move on. The ones who watched this see straight into how AI actually works. Bookmark & Watch it today, this one's a legend ↓

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429,948 次观看 • 17 天前

.Oprah Winfrey: For all of you watching who are still on the fence, in the middle, independent as I am, or whether you just still don't know what you're gonna do. This is the moment for all decent and caring people who want the best for yourself and other people. This is the moment for people who are tired of all of the bickering and all of the name-calling, people who are exhausted by the craziness and the made up stories and the conspiracies. This is the moment you wanna get on with your life because you know that we can do better and that we deserve better. You know this, I know you know this, I know you feel this. I know this is what you're saying amongst yourselves. We're better than this. And as my friend and mentor Maya Angelou always said, ‘When you know better, you got to do better.’ So let's do better and vote for Kamala Harris

.Oprah Winfrey: For all of you watching who are still on the fence, in the middle, independent as I am, or whether you just still don't know what you're gonna do. This is the moment for all decent and caring people who want the best for yourself and other people. This is the moment for people who are tired of all of the bickering and all of the name-calling, people who are exhausted by the craziness and the made up stories and the conspiracies. This is the moment you wanna get on with your life because you know that we can do better and that we deserve better. You know this, I know you know this, I know you feel this. I know this is what you're saying amongst yourselves. We're better than this. And as my friend and mentor Maya Angelou always said, ‘When you know better, you got to do better.’ So let's do better and vote for Kamala Harris

Headquarters

2,490,325 次观看 • 1 年前

Coinbase CEO Explains “Reverse Prompting” and the Rise of the AI CEO Brian Armstrong: “One of the big pushes we made in the last year was we got our own internal hosted AI model that was connected to all of our data sources, right?” “So it's like every Slack message, every Google doc, Salesforce data, Confluence, you know.” “So now the data is all aggregated and I've started to ask it really… it's not just like prompting it, ‘Hey, can you write this kind of memo for me,’ or something.” “I'm asking these AI agents now, ‘As CEO, what should I be aware of in the company that I might not be aware of?’ And it'll tell me, ‘Did you know that there's actually disagreement on this team about the strategy?’ And I was like, actually, I didn't know that.” “This is like reverse prompting. So instead of telling the AI agent what you want it to do, you ask it what you should be thinking more about.” @jason: “It's a mentor. It's a coach.” Brian: “Yeah. Like, what could make me a better CEO? And it's like, ‘Well, I looked at how you spent your time in the last quarter and here's how you said that you wanted to spend it, but you actually spent 32% of your time on this instead of 20%.’” “I've asked it other questions like, ‘What's the thing that I changed my mind on the most over the last year?’ Things like that.” “It'll prompt you with information you should be thinking about instead of the other way around.” Thanks to our partner for making this happen!: Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE 🏛.

Coinbase CEO Explains “Reverse Prompting” and the Rise of the AI CEO Brian Armstrong: “One of the big pushes we made in the last year was we got our own internal hosted AI model that was connected to all of our data sources, right?” “So it's like every Slack message, every Google doc, Salesforce data, Confluence, you know.” “So now the data is all aggregated and I've started to ask it really… it's not just like prompting it, ‘Hey, can you write this kind of memo for me,’ or something.” “I'm asking these AI agents now, ‘As CEO, what should I be aware of in the company that I might not be aware of?’ And it'll tell me, ‘Did you know that there's actually disagreement on this team about the strategy?’ And I was like, actually, I didn't know that.” “This is like reverse prompting. So instead of telling the AI agent what you want it to do, you ask it what you should be thinking more about.” @jason: “It's a mentor. It's a coach.” Brian: “Yeah. Like, what could make me a better CEO? And it's like, ‘Well, I looked at how you spent your time in the last quarter and here's how you said that you wanted to spend it, but you actually spent 32% of your time on this instead of 20%.’” “I've asked it other questions like, ‘What's the thing that I changed my mind on the most over the last year?’ Things like that.” “It'll prompt you with information you should be thinking about instead of the other way around.” Thanks to our partner for making this happen!: Our episode is sponsored by the New York Stock Exchange - a modern marketplace and exchange for building the future. It all happens at the NYSE 🏛.

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80,524 次观看 • 5 个月前

Darko on Brandon Ingram’s defence improving over the season: “Everything started in the Summer League. When he saw our summer league team play and how they were aggressive, he was like, ‘whoa.’ He was impressed there and he took it very seriously; that he needs to step up on that side of the floor.” “What I can tell you about Brandon Ingram is that, he’s an absolute team guy, and he’s an absolute winner. All he wants to do is win. If that demands to step out on the defensive end, he’s not shying away from there.” “He’s doing an outstanding job for us defensively, and we want him to be 1% better for the next game.”

Darko on Brandon Ingram’s defence improving over the season: “Everything started in the Summer League. When he saw our summer league team play and how they were aggressive, he was like, ‘whoa.’ He was impressed there and he took it very seriously; that he needs to step up on that side of the floor.” “What I can tell you about Brandon Ingram is that, he’s an absolute team guy, and he’s an absolute winner. All he wants to do is win. If that demands to step out on the defensive end, he’s not shying away from there.” “He’s doing an outstanding job for us defensively, and we want him to be 1% better for the next game.”

Omer Osman

34,198 次观看 • 6 个月前

how beautiful it must be to have someone in your life that supports you every step of the way and does it all just because he loves you and is proud of you

how beautiful it must be to have someone in your life that supports you every step of the way and does it all just because he loves you and is proud of you

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the engineer who built Claude Code just dropped a 28-minute video on how to write prompts that actually work I've seen $300 courses that don't cover what he shows in the first 10 minutes CLAUDE.md files, memory shortcuts, parallel sessions, prompting patterns all in one video and completely free after watching this, the next step is agents I wrote a full guide on how to build one yourself with Claude Code article below

the engineer who built Claude Code just dropped a 28-minute video on how to write prompts that actually work I've seen $300 courses that don't cover what he shows in the first 10 minutes CLAUDE.md files, memory shortcuts, parallel sessions, prompting patterns all in one video and completely free after watching this, the next step is agents I wrote a full guide on how to build one yourself with Claude Code article below

Anatoli Kopadze

1,248,095 次观看 • 28 天前

Boris Cherny, the creator of Claude Code at Anthropic, just explained why he stopped prompting Claude entirely in this talk he breaks down exactly how the future is teams of agents, not better prompts: - the 14% you lose to CLAUDE.md before typing a word - the features that change how Claude thinks before you type a word - the features most Claude users don't know exist - why typing prompts one at a time is already the slow lane Boris Cherny: "Now I don’t prompt Claude anymore - I have loops that are running. My job is to write loops." if you've been using Claude for more than a month and never left the chat window, you have at least 23 untouched features. probably 25 instead of another show tonight, watch this make sure to bookmark it before it gets lost in your feed my breakdown of all 25 features is below

Boris Cherny, the creator of Claude Code at Anthropic, just explained why he stopped prompting Claude entirely in this talk he breaks down exactly how the future is teams of agents, not better prompts: - the 14% you lose to CLAUDE.md before typing a word - the features that change how Claude thinks before you type a word - the features most Claude users don't know exist - why typing prompts one at a time is already the slow lane Boris Cherny: "Now I don’t prompt Claude anymore - I have loops that are running. My job is to write loops." if you've been using Claude for more than a month and never left the chat window, you have at least 23 untouched features. probably 25 instead of another show tonight, watch this make sure to bookmark it before it gets lost in your feed my breakdown of all 25 features is below

Khairallah AL-Awady

102,529 次观看 • 1 个月前

Anthropic engineer: "Fable 5 is already smarter than we know how to use. The bottleneck was never the AI, it's you." In 19 minutes he shows exactly how to get everything out of Claude with no extra tools, no extra costs. You're already paying for all of this, just not using it. Watch the session, then read the guide below on the Claude features 99% of users never find.

Anthropic engineer: "Fable 5 is already smarter than we know how to use. The bottleneck was never the AI, it's you." In 19 minutes he shows exactly how to get everything out of Claude with no extra tools, no extra costs. You're already paying for all of this, just not using it. Watch the session, then read the guide below on the Claude features 99% of users never find.

Anatoli Kopadze

388,375 次观看 • 1 天前

Church, why are we celebrating or partaking in ANYTHING on October 31st? Ask yourself, how is anything you are doing on that day honoring God? We are in this world church, not of it. We are commanded to know our enemy and know what he is doing in this evil world. Unfortunately ALL of our “holidays” have pagan roots because satan is the god of this world and it is his desire- every single second of every single day- to drive you and your family away from Christ and away from the Word.

Church, why are we celebrating or partaking in ANYTHING on October 31st? Ask yourself, how is anything you are doing on that day honoring God? We are in this world church, not of it. We are commanded to know our enemy and know what he is doing in this evil world. Unfortunately ALL of our “holidays” have pagan roots because satan is the god of this world and it is his desire- every single second of every single day- to drive you and your family away from Christ and away from the Word.

Ashley Hays

31,169 次观看 • 8 个月前

.Naval: Epistemology, which is a fancy word for the theory of how knowledge grows or how knowledge growth occurs. And we've all been told since we're young that there's a scientific method and that scientists sort of do this stuff in white lab coats and we're supposed to accept it because of this thing called the scientific method. And then they give us true beliefs that we can then say, well the science is settled and we take that we move on. And we all only have a very, very vague understanding of how this works. And people say, well maybe you go out in the real world, you look at what's happening, you make all these observations, and then based on that you form a theory, you test the theory against more observations, and the more observations you get the closer you get to the truth. And once you have enough observation it's true and then you call it a scientific theory or a law and it's settled and you move on. And this is the popular conception of how science works. And as Popper pointed out and as you take even further, this is completely wrong. And so I'd love for you to get into that, which is what is knowledge? How does it grow? What is the real scientific method? And how do we figure things out? David Deutsch: I love the way you just stated the prevailing view there and laced every aspect of it with the contempt that it deserves. So you just went through touching every base. It's amazing that this series of misconceptions is still common sense. I mean, that it was common sense at a time when we didn't really have science or when science was just starting up, when the main issue in science was freeing itself from dogmatism, freeing itself from religion, freeing itself from authority, and so on. There it was understandable that people would look for an alternative source of authority and they would think, oh, it's sense impressions. We can see the world and you know, these religious people, they can't even see God and so on. And so we are confined to what we can see. That's where we get our ideas from. And as you say, that is completely false. Sense impressions, like all observation, even the most careful scientific observation is all theory laden. And theories are inherently fallible. I mean, we actually want to replace our best theories. Everybody who does a PhD is technically anyway, working to overturn something in the existing body of knowledge. You're not turned away at the door if you say, I don't believe this stuff, I'm going to produce something better. Whereas for most of human history, that was exactly what you were forbidden to do. The idea was that we already had all the important knowledge. If you want to discover something new, what you had to make sure of was that it didn't contradict the existing knowledge. Now, you have to make sure that it does contradict existing knowledge. So more or less. Naval: Yeah, it's this tradition of criticism that you've talked about in the West, that the Enlightenment really ushered in the Enlightenment era. David Deutsch: It has been institutionalized. So in many ways, our institutions are wiser than we are. So the institutions of science, for instance, have this built in, even if scientists actually don't always act that way. In fact, they often don't act that way, and act in a dogmatic way and try to preserve the status quo and are resistant to new ideas and so on. But the institutions, the way the procedures of science work, makes the right thing happen in the end anyway, regardless of what the people are trying to do. Naval: So you're saying the knowledge of the true scientific method is embedded in the institutions of science in the PhD process? David Deutsch: Well, the best scientific method that we know of, and one shouldn't really think of it as a method, you know, there's this wonderful lecture by Popper when he first was made a professor at the London School of Economics. He was made a professor of scientific method, and his first six lectures, I wish the rest of them were, the first six lectures are on the internet somewhere. And he starts the first one by saying, I am the first professor of scientific method in the British Empire. The British Empire still existed at the time, more or less. And so the first thing I want to say to you is that there is no such thing as the scientific method. And then he goes on from there. So this subject does not exist. So if any of you have come here to learn the handle that you have to turn in order to make scientific knowledge come out the other end, you're going to be disappointed.

.Naval: Epistemology, which is a fancy word for the theory of how knowledge grows or how knowledge growth occurs. And we've all been told since we're young that there's a scientific method and that scientists sort of do this stuff in white lab coats and we're supposed to accept it because of this thing called the scientific method. And then they give us true beliefs that we can then say, well the science is settled and we take that we move on. And we all only have a very, very vague understanding of how this works. And people say, well maybe you go out in the real world, you look at what's happening, you make all these observations, and then based on that you form a theory, you test the theory against more observations, and the more observations you get the closer you get to the truth. And once you have enough observation it's true and then you call it a scientific theory or a law and it's settled and you move on. And this is the popular conception of how science works. And as Popper pointed out and as you take even further, this is completely wrong. And so I'd love for you to get into that, which is what is knowledge? How does it grow? What is the real scientific method? And how do we figure things out? David Deutsch: I love the way you just stated the prevailing view there and laced every aspect of it with the contempt that it deserves. So you just went through touching every base. It's amazing that this series of misconceptions is still common sense. I mean, that it was common sense at a time when we didn't really have science or when science was just starting up, when the main issue in science was freeing itself from dogmatism, freeing itself from religion, freeing itself from authority, and so on. There it was understandable that people would look for an alternative source of authority and they would think, oh, it's sense impressions. We can see the world and you know, these religious people, they can't even see God and so on. And so we are confined to what we can see. That's where we get our ideas from. And as you say, that is completely false. Sense impressions, like all observation, even the most careful scientific observation is all theory laden. And theories are inherently fallible. I mean, we actually want to replace our best theories. Everybody who does a PhD is technically anyway, working to overturn something in the existing body of knowledge. You're not turned away at the door if you say, I don't believe this stuff, I'm going to produce something better. Whereas for most of human history, that was exactly what you were forbidden to do. The idea was that we already had all the important knowledge. If you want to discover something new, what you had to make sure of was that it didn't contradict the existing knowledge. Now, you have to make sure that it does contradict existing knowledge. So more or less. Naval: Yeah, it's this tradition of criticism that you've talked about in the West, that the Enlightenment really ushered in the Enlightenment era. David Deutsch: It has been institutionalized. So in many ways, our institutions are wiser than we are. So the institutions of science, for instance, have this built in, even if scientists actually don't always act that way. In fact, they often don't act that way, and act in a dogmatic way and try to preserve the status quo and are resistant to new ideas and so on. But the institutions, the way the procedures of science work, makes the right thing happen in the end anyway, regardless of what the people are trying to do. Naval: So you're saying the knowledge of the true scientific method is embedded in the institutions of science in the PhD process? David Deutsch: Well, the best scientific method that we know of, and one shouldn't really think of it as a method, you know, there's this wonderful lecture by Popper when he first was made a professor at the London School of Economics. He was made a professor of scientific method, and his first six lectures, I wish the rest of them were, the first six lectures are on the internet somewhere. And he starts the first one by saying, I am the first professor of scientific method in the British Empire. The British Empire still existed at the time, more or less. And so the first thing I want to say to you is that there is no such thing as the scientific method. And then he goes on from there. So this subject does not exist. So if any of you have come here to learn the handle that you have to turn in order to make scientific knowledge come out the other end, you're going to be disappointed.

Deutsch Explains

114,992 次观看 • 1 年前

🎙️ Del Bigtree on the moment everything changed. It was supposed to be just another segment on The Doctors. A senator walks on stage to announce a forced vaccination bill, and something in Del Bigtree snapped. "It was a God moment for me. It woke up a monster that I don't think anyone really wanted to deal with." Del had spent years behind the scenes on one of television's biggest medical talk shows, never having been to a doctor in his life. His mom couldn't figure out why he was there. He says now he understands: he was there to learn exactly how the machine works. How they make you afraid of disease. How they sell pharmaceutical products by manufacturing fear. How a "flu outbreak" segment is produced to maximize panic. He watched it happen from the inside. And then he decided to use everything he learned to flip the script. "The simplest way to undo this wrong is to show you that you should be afraid of the vaccine too." If you're scared of measles, Del wants you to know there's a real chance the measles vaccine is even more dangerous. So he made a film called Vaxxed to show you exactly what that means. The mission that has never stopped: You will never force-vaccinate my kids. Or me. A decade later, he's still on that mission. And the momentum has never been stronger. 👉 Watch the full clip at

🎙️ Del Bigtree on the moment everything changed. It was supposed to be just another segment on The Doctors. A senator walks on stage to announce a forced vaccination bill, and something in Del Bigtree snapped. "It was a God moment for me. It woke up a monster that I don't think anyone really wanted to deal with." Del had spent years behind the scenes on one of television's biggest medical talk shows, never having been to a doctor in his life. His mom couldn't figure out why he was there. He says now he understands: he was there to learn exactly how the machine works. How they make you afraid of disease. How they sell pharmaceutical products by manufacturing fear. How a "flu outbreak" segment is produced to maximize panic. He watched it happen from the inside. And then he decided to use everything he learned to flip the script. "The simplest way to undo this wrong is to show you that you should be afraid of the vaccine too." If you're scared of measles, Del wants you to know there's a real chance the measles vaccine is even more dangerous. So he made a film called Vaxxed to show you exactly what that means. The mission that has never stopped: You will never force-vaccinate my kids. Or me. A decade later, he's still on that mission. And the momentum has never been stronger. 👉 Watch the full clip at

The HighWire

51,042 次观看 • 4 个月前