正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

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 ↓show more

slash1s

9,860 subscribers

358,660 次观看 • 2 个月前 •via X (Twitter)

艺术教育科学技术

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Boris Cherny, the creator of Claude Code at Anthropic, just explained how he runs thousands of agents from his phone while he sleeps in this talk he breaks down exactly how he manages thousands of agents from his phone: - the 14% you lose to CLAUDE.md before typing a word - the architecture behind running a few thousand agents overnight - why the system matters more than the tool - the knowledge structure that makes everything findable, connected, and useful if you've been using Claude for months and every conversation still starts from scratch with zero memory and zero context, you don't have a system. you have a chat history instead of another show tonight, watch this make sure to bookmark it before it gets lost in your feed the guide is in the article below

Boris Cherny, the creator of Claude Code at Anthropic, just explained how he runs thousands of agents from his phone while he sleeps in this talk he breaks down exactly how he manages thousands of agents from his phone: - the 14% you lose to CLAUDE.md before typing a word - the architecture behind running a few thousand agents overnight - why the system matters more than the tool - the knowledge structure that makes everything findable, connected, and useful if you've been using Claude for months and every conversation still starts from scratch with zero memory and zero context, you don't have a system. you have a chat history instead of another show tonight, watch this make sure to bookmark it before it gets lost in your feed the guide is in the article below

Khairallah AL-Awady

86,328 次观看 • 2 个月前

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 ↓

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 ↓

slash1s

685,710 次观看 • 1 个月前

Andrej Karpathy spent 2h showing how he actually uses AI day to day he's a co-founder of OpenAI and led AI at Tesla, so when he shows how he works, it’s worth watching and the whole session is just him telling the machine what he wants in simple terms, like he's briefing a coworker watch what's actually happening the entire time: > he describes the task in normal words > it goes off and does the work > he glances at the result and nudges it with one more sentence that's the whole skill, and you've had it since you learned to talk the only gap between that and a worker that runs on its own is handing that sentence a schedule and the tools to act check his work, then build the version that keeps working when you stop

Andrej Karpathy spent 2h showing how he actually uses AI day to day he's a co-founder of OpenAI and led AI at Tesla, so when he shows how he works, it’s worth watching and the whole session is just him telling the machine what he wants in simple terms, like he's briefing a coworker watch what's actually happening the entire time: > he describes the task in normal words > it goes off and does the work > he glances at the result and nudges it with one more sentence that's the whole skill, and you've had it since you learned to talk the only gap between that and a worker that runs on its own is handing that sentence a schedule and the tools to act check his work, then build the version that keeps working when you stop

Chrome

1,802,218 次观看 • 2 个月前

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

99,512 次观看 • 1 个月前

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 ↓

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 ↓

slash1s

433,140 次观看 • 1 个月前

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

293,652 次观看 • 1 个月前

A DEVELOPER TAUGHT GIT WITH A BOX OF CHILDREN'S TOYS AND ENGINEERS WITH TEN YEARS IN SAY IT'S THE FIRST TIME THE THING EVER ACTUALLY MADE SENSE 90 minutes, one table, a pile of Tinkertoys. No wall of jargon -- he builds a real Git repo out of plastic rods right in front of you. -> The moment he snaps the first pieces together, Git stops being scary command-line magic and becomes what it really is: a chain of tiny objects pointing at each other. Branches, merges, rebase, the staging area -- every concept that's ever burned you at 2am -- he rebuilds with toys until a four year old could follow. He calls Git a two-trick pony. After this you'll see exactly why. Memorizing commands was never the skill -> holding the graph in your head is. And with an AI agent now committing and rebasing on your machine all day, that mental model is the only thing between you and a history you can't read. Scroll the comments and you'll see the same thing over and over: this is the talk that finally made Git click and made people the one their whole team comes to when it breaks. Bookmark & watch it today. It's the 1.5 hours that pays you back for the rest of your career ↓

A DEVELOPER TAUGHT GIT WITH A BOX OF CHILDREN'S TOYS AND ENGINEERS WITH TEN YEARS IN SAY IT'S THE FIRST TIME THE THING EVER ACTUALLY MADE SENSE 90 minutes, one table, a pile of Tinkertoys. No wall of jargon -- he builds a real Git repo out of plastic rods right in front of you. -> The moment he snaps the first pieces together, Git stops being scary command-line magic and becomes what it really is: a chain of tiny objects pointing at each other. Branches, merges, rebase, the staging area -- every concept that's ever burned you at 2am -- he rebuilds with toys until a four year old could follow. He calls Git a two-trick pony. After this you'll see exactly why. Memorizing commands was never the skill -> holding the graph in your head is. And with an AI agent now committing and rebasing on your machine all day, that mental model is the only thing between you and a history you can't read. Scroll the comments and you'll see the same thing over and over: this is the talk that finally made Git click and made people the one their whole team comes to when it breaks. Bookmark & watch it today. It's the 1.5 hours that pays you back for the rest of your career ↓

slash1s

227,323 次观看 • 2 个月前

A screen recording is the best context you can give an AI agent. It's also the worst. A few seconds of video is thousands of images. Feed that to an agent and you instantly blow up its memory. So I built a tool that fixes it. How it works: Hit record and just do your thing. Click around, type, and talk out loud about what you're doing. While you record, it quietly captures the stuff that actually matters: your voice transcription, every click and the exact thing you clicked, what you typed, and the shortcuts you press. When you stop, it doesn't hand the agent the whole video. It writes a short, readable summary: a timeline of what you said and did. The agent reads that tiny summary first. Then, only when it needs to actually see a moment, it pulls that one exact frame from the video, like flipping to a single page instead of reading the whole book. The result: the agent understands everything you did! Full context. Less tokens.

A screen recording is the best context you can give an AI agent. It's also the worst. A few seconds of video is thousands of images. Feed that to an agent and you instantly blow up its memory. So I built a tool that fixes it. How it works: Hit record and just do your thing. Click around, type, and talk out loud about what you're doing. While you record, it quietly captures the stuff that actually matters: your voice transcription, every click and the exact thing you clicked, what you typed, and the shortcuts you press. When you stop, it doesn't hand the agent the whole video. It writes a short, readable summary: a timeline of what you said and did. The agent reads that tiny summary first. Then, only when it needs to actually see a moment, it pulls that one exact frame from the video, like flipping to a single page instead of reading the whole book. The result: the agent understands everything you did! Full context. Less tokens.

Milind S

12,376 次观看 • 1 个月前

Shameful and Disgusting! Trump using extremely derogatory language against Saudi Crown Prince MBS. Is this how you talk about the head of a state, one of your greatest allies? I could not believe it, so I had to watch the full speech, and here is the full version of what he said.

Shameful and Disgusting! Trump using extremely derogatory language against Saudi Crown Prince MBS. Is this how you talk about the head of a state, one of your greatest allies? I could not believe it, so I had to watch the full speech, and here is the full version of what he said.

Saniya Sayed

201,432 次观看 • 4 个月前

Notch Clips. every other ad tool ignores the footage sitting in your dropbox and generates new clips from a prompt. notch opens your library instead. it watches every clip you have ever shot and understands what is inside each one. the mood. who is in frame. what they are doing. the quality. so when you ask it to build an ad, it does not start from scratch. it reaches into your past shoots, finds the clip that fits, and slots it into the exact moment that needs it. here is what that looks like. you had thirteen versions of one reaction shot. notch picked the one that worked and left the other twelve. not by filename. not by guessing from a reference image. it watched all thirteen and could tell the difference. that is the whole idea. the right clip was already in your library. every other tool was about to make a worse one. footage you already shot, turned into every ad you still need. drop your site and a few clips you have. notch builds the first ad from them.

Notch Clips. every other ad tool ignores the footage sitting in your dropbox and generates new clips from a prompt. notch opens your library instead. it watches every clip you have ever shot and understands what is inside each one. the mood. who is in frame. what they are doing. the quality. so when you ask it to build an ad, it does not start from scratch. it reaches into your past shoots, finds the clip that fits, and slots it into the exact moment that needs it. here is what that looks like. you had thirteen versions of one reaction shot. notch picked the one that worked and left the other twelve. not by filename. not by guessing from a reference image. it watched all thirteen and could tell the difference. that is the whole idea. the right clip was already in your library. every other tool was about to make a worse one. footage you already shot, turned into every ad you still need. drop your site and a few clips you have. notch builds the first ad from them.

Vinay Jain

406,286 次观看 • 2 个月前

David Tepper explained what actually builds your career in the markets. and it's definitely not a perfect track record talking to students, he was straight up: your success just depends on how you bounce back from taking a hit "if i go through my career, it was a lot of disappointments. there's a lot of things that didn't go right. but that's not what's gonna define you. what's gonna define you is how you recover from those things and how you move on. you just never stop." another solid lesson from Tepper is about staying true to yourself. when he was at Goldman Sachs, the head of M&A told him to buy a stock that was on the firm's restricted list. Tepper just flat out refused to do the trade. because of that, the guy killed Tepper's chance of making partner later on. but he has zero regrets: if someone tells you to do something sketchy, just don't do it, even if it hurts your career the takeaway: the markets will inevitably punch you in the face. the key is not to get stuck, learn from it, and keep moving forward bookmark and watch the full talk here

David Tepper explained what actually builds your career in the markets. and it's definitely not a perfect track record talking to students, he was straight up: your success just depends on how you bounce back from taking a hit "if i go through my career, it was a lot of disappointments. there's a lot of things that didn't go right. but that's not what's gonna define you. what's gonna define you is how you recover from those things and how you move on. you just never stop." another solid lesson from Tepper is about staying true to yourself. when he was at Goldman Sachs, the head of M&A told him to buy a stock that was on the firm's restricted list. Tepper just flat out refused to do the trade. because of that, the guy killed Tepper's chance of making partner later on. but he has zero regrets: if someone tells you to do something sketchy, just don't do it, even if it hurts your career the takeaway: the markets will inevitably punch you in the face. the key is not to get stuck, learn from it, and keep moving forward bookmark and watch the full talk here

ludoonchart

325,530 次观看 • 1 个月前

Marvin Minsky, MIT professor and father of artificial intelligence: "Anthropic pays engineers $900K to build multi-agent AI systems. The blueprint is 40 years old, from an MIT professor who proved intelligence is just a swarm of dumb specialists." the thread above shows you how to turn one AI into a team of specialized agents, each with its own job and memory, all managed by a boss. brilliant. it is also marvin minsky's 1986 theory of how your own mind works. minsky's whole idea was that intelligence is not one smart thing. it is a society of tiny, mindless agents, each doing a single dumb job, none of them intelligent alone. put enough of them together under a few managers and intelligence emerges. that is not a metaphor for the claude trick. it is the claude trick. so when you spin up specialized sub-agents and delegate, you are not inventing a new hack. you are rebuilding the architecture minsky described forty years ago, the same one your brain has run your entire life. he co-founded the field, taught it at MIT, and left it all in this free lecture. same story i keep telling: the "new" AI trick is usually an old idea in a new wrapper. here is the part the thread skips, and minsky knew it. a society of agents is only as good as how you organize it. one dumb specialist is useless. a thousand, badly managed, is chaos. the edge was never spawning the agents. it is the orchestration, knowing which specialist to call, when, and how to combine their answers. the tool is free. the judgment is the whole game.

Marvin Minsky, MIT professor and father of artificial intelligence: "Anthropic pays engineers $900K to build multi-agent AI systems. The blueprint is 40 years old, from an MIT professor who proved intelligence is just a swarm of dumb specialists." the thread above shows you how to turn one AI into a team of specialized agents, each with its own job and memory, all managed by a boss. brilliant. it is also marvin minsky's 1986 theory of how your own mind works. minsky's whole idea was that intelligence is not one smart thing. it is a society of tiny, mindless agents, each doing a single dumb job, none of them intelligent alone. put enough of them together under a few managers and intelligence emerges. that is not a metaphor for the claude trick. it is the claude trick. so when you spin up specialized sub-agents and delegate, you are not inventing a new hack. you are rebuilding the architecture minsky described forty years ago, the same one your brain has run your entire life. he co-founded the field, taught it at MIT, and left it all in this free lecture. same story i keep telling: the "new" AI trick is usually an old idea in a new wrapper. here is the part the thread skips, and minsky knew it. a society of agents is only as good as how you organize it. one dumb specialist is useless. a thousand, badly managed, is chaos. the edge was never spawning the agents. it is the orchestration, knowing which specialist to call, when, and how to combine their answers. the tool is free. the judgment is the whole game.

Rossst.03

147,913 次观看 • 24 天前

A DEVELOPER STOOD UP AT A CONFERENCE AND APOLOGIZED TO THE ENTIRE INDUSTRY FOR ONE LINE OF CODE HE WROTE IN 1965. THAT SINGLE DECISION HAS SINCE CAUSED CRASHES, BREACHES AND ROUGHLY A BILLION DOLLARS OF DAMAGE AND YOU HIT IT EVERY SINGLE DAY 61 minutes from Tony Hoare -- the man who invented quicksort, won the Turing Award, and passed away in early 2026, leaving this as one of his most honest talks. -> His confession: he added the null reference, letting any variable secretly mean "nothing", simply because it was easy to implement. That one shortcut became the null pointer, the undefined, the None -- the crash waiting inside almost every program ever written. He calls it his billion-dollar mistake, and he is not exaggerating. Whole classes of bugs and security holes trace straight back to it. And this is the deeper lesson under the AI rush: the easy shortcut you ship today becomes the landmine everyone steps on for the next 40 years. You thought null was just part of how code works. This is the talk where the man who made it tells you it never had to be. Bookmark & Watch this one. You'll never type null the same way ↓

A DEVELOPER STOOD UP AT A CONFERENCE AND APOLOGIZED TO THE ENTIRE INDUSTRY FOR ONE LINE OF CODE HE WROTE IN 1965. THAT SINGLE DECISION HAS SINCE CAUSED CRASHES, BREACHES AND ROUGHLY A BILLION DOLLARS OF DAMAGE AND YOU HIT IT EVERY SINGLE DAY 61 minutes from Tony Hoare -- the man who invented quicksort, won the Turing Award, and passed away in early 2026, leaving this as one of his most honest talks. -> His confession: he added the null reference, letting any variable secretly mean "nothing", simply because it was easy to implement. That one shortcut became the null pointer, the undefined, the None -- the crash waiting inside almost every program ever written. He calls it his billion-dollar mistake, and he is not exaggerating. Whole classes of bugs and security holes trace straight back to it. And this is the deeper lesson under the AI rush: the easy shortcut you ship today becomes the landmine everyone steps on for the next 40 years. You thought null was just part of how code works. This is the talk where the man who made it tells you it never had to be. Bookmark & Watch this one. You'll never type null the same way ↓

slash1s

278,746 次观看 • 1 个月前

MICROSOFT PUT THE ENTIRE SOURCE CODE OF WINDOWS INTO A SINGLE GIT REPO -- 300 GIGABYTES, 3.5 MILLION FILES AND MADE IT CLONE IN SECONDS 31 minutes from the Microsoft engineer who actually did it, bending the tool you use for a 50-file side project to hold the biggest codebase on the planet. -> The moment it lands, every excuse dies. You've heard "Git doesn't scale, use something else" your whole career. They ran git status on the largest repo alive and it came back instantly. The secret wasn't a different tool. It was understanding what git actually stores and realizing you never need the whole thing on disk. Pull only the files you touch. Ignore the 3.4 million you never will. Knowing the commands was never the ceiling -> understanding how git stores and moves things is what lets you do what everyone swears is impossible. And as AI agents spin up repos that balloon overnight, knowing how git scales is what keeps you from drowning in your own history. Everyone treats git like it maxes out at a hobby project. One team quietly proved it can hold an operating system. Bookmark & Watch it today ↓

MICROSOFT PUT THE ENTIRE SOURCE CODE OF WINDOWS INTO A SINGLE GIT REPO -- 300 GIGABYTES, 3.5 MILLION FILES AND MADE IT CLONE IN SECONDS 31 minutes from the Microsoft engineer who actually did it, bending the tool you use for a 50-file side project to hold the biggest codebase on the planet. -> The moment it lands, every excuse dies. You've heard "Git doesn't scale, use something else" your whole career. They ran git status on the largest repo alive and it came back instantly. The secret wasn't a different tool. It was understanding what git actually stores and realizing you never need the whole thing on disk. Pull only the files you touch. Ignore the 3.4 million you never will. Knowing the commands was never the ceiling -> understanding how git stores and moves things is what lets you do what everyone swears is impossible. And as AI agents spin up repos that balloon overnight, knowing how git scales is what keeps you from drowning in your own history. Everyone treats git like it maxes out at a hobby project. One team quietly proved it can hold an operating system. Bookmark & Watch it today ↓

slash1s

255,565 次观看 • 2 个月前

Eric Schmidt on what he calls "the San Francisco consensus": "There's a group of people that I work with. They're all in San Francisco and they've all basically convinced themselves that in the next two to four year, the average is three years the entire world will change." He's careful to flag the catch in that word "consensus": "It's true that it's a consensus, but it's not necessarily true that the consensus is true." So why do these people believe it? Eric walks through the reasoning. First came language-to-language models. "ChatGPT is the best one, they did a great job," he says, with everyone else catching up. Then came two additions: reasoning, and memory inside these systems. Put those together and you get what he calls the agentic revolution: "The agentic revolution… can be understood as language in, memory and language, language out." To make it concrete, he uses a deliberately mundane example. Say he wants to build a house in California. One agent finds the lot. Another works out the rules. Another designs the building. Another selects the contractor. And, at least in America, another agent sues the contractor when the house doesn't work. The point of such a "stupid example," as he puts it, is exactly that it's ordinary: "I just gave you a workflow example that's true of every business, every government and every group human activity." That's why he thinks the consensus carries weight: "When you understand that the agentic revolution and the reasoning revolution together really changed the way we operate as humans, then you understand why the San Francisco consensus is so powerful." On the reasoning side, he points to models that work a problem forward and backward: "It will blow your mind away, especially when you ask it a question that you have no idea what the question is about and you watch it reason." And he cites the numbers he's seeing: "Google now has a math model that is at the 90 percentile of math graduate students." More broadly, he claims, "we now have systems now that are 90% of all of the graduate school skills. You know, math, physics, and so forth." When something can do that, he argues, "it will happen at a big scale." This is where the consensus reaches its sharpest point: recursive self-improvement. "There's a moment when what is called recursive self-improvement, the system begins to learn on itself, where it goes forward at a rate that is impossible for us to understand. It becomes combinatorial in a way that we as humans do not understand." His verdict on all of it is two-sided: "This is both incredibly exciting and also very worrisome."

Eric Schmidt on what he calls "the San Francisco consensus": "There's a group of people that I work with. They're all in San Francisco and they've all basically convinced themselves that in the next two to four year, the average is three years the entire world will change." He's careful to flag the catch in that word "consensus": "It's true that it's a consensus, but it's not necessarily true that the consensus is true." So why do these people believe it? Eric walks through the reasoning. First came language-to-language models. "ChatGPT is the best one, they did a great job," he says, with everyone else catching up. Then came two additions: reasoning, and memory inside these systems. Put those together and you get what he calls the agentic revolution: "The agentic revolution… can be understood as language in, memory and language, language out." To make it concrete, he uses a deliberately mundane example. Say he wants to build a house in California. One agent finds the lot. Another works out the rules. Another designs the building. Another selects the contractor. And, at least in America, another agent sues the contractor when the house doesn't work. The point of such a "stupid example," as he puts it, is exactly that it's ordinary: "I just gave you a workflow example that's true of every business, every government and every group human activity." That's why he thinks the consensus carries weight: "When you understand that the agentic revolution and the reasoning revolution together really changed the way we operate as humans, then you understand why the San Francisco consensus is so powerful." On the reasoning side, he points to models that work a problem forward and backward: "It will blow your mind away, especially when you ask it a question that you have no idea what the question is about and you watch it reason." And he cites the numbers he's seeing: "Google now has a math model that is at the 90 percentile of math graduate students." More broadly, he claims, "we now have systems now that are 90% of all of the graduate school skills. You know, math, physics, and so forth." When something can do that, he argues, "it will happen at a big scale." This is where the consensus reaches its sharpest point: recursive self-improvement. "There's a moment when what is called recursive self-improvement, the system begins to learn on itself, where it goes forward at a rate that is impossible for us to understand. It becomes combinatorial in a way that we as humans do not understand." His verdict on all of it is two-sided: "This is both incredibly exciting and also very worrisome."

High Signal AI

31,085 次观看 • 2 个月前

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 ↓

slash1s

22,107 次观看 • 1 个月前

"It's embarrassing because the best guy in professional wrestling today is not a wrestler... Logan Paul is a star. Unbelievable. You talk about the IT factor. This guy reeks of IT. The fact of how long he's been doing this and how good he is... That should challenge every professional wrestler out there." Vince Russo shares who he thinks is the top talent in WWE today.

"It's embarrassing because the best guy in professional wrestling today is not a wrestler... Logan Paul is a star. Unbelievable. You talk about the IT factor. This guy reeks of IT. The fact of how long he's been doing this and how good he is... That should challenge every professional wrestler out there." Vince Russo shares who he thinks is the top talent in WWE today.

Ariel Helwani

823,770 次观看 • 8 个月前

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 次观看 • 2 个月前

Ilya Sutskever, co-founder and chief scientist of OpenAI: "The better a neural network can predict the next word, the more it understands it." Everyone calls it autocomplete. Ilya explained why that is a comforting lie. To guess the final word of a murder mystery, the name of the killer, the model has to reason through every clue in the book. Prediction that good is not statistics. It is understanding. Then he said the part that should stop you. The text these models train on is "a projection of the world," and to compress it they learn more and more about people, "the human condition, their hopes, dreams, and motivations." The machine is not memorizing our words. It is quietly building a model of us. That is the whole premise of the fear. The machine will never hate you. It understands you far better than that. The frightening variable was never the intelligence. It was the aim. I wrote the full story: the one fear about AI everyone gets wrong, and the one already here.

Ilya Sutskever, co-founder and chief scientist of OpenAI: "The better a neural network can predict the next word, the more it understands it." Everyone calls it autocomplete. Ilya explained why that is a comforting lie. To guess the final word of a murder mystery, the name of the killer, the model has to reason through every clue in the book. Prediction that good is not statistics. It is understanding. Then he said the part that should stop you. The text these models train on is "a projection of the world," and to compress it they learn more and more about people, "the human condition, their hopes, dreams, and motivations." The machine is not memorizing our words. It is quietly building a model of us. That is the whole premise of the fear. The machine will never hate you. It understands you far better than that. The frightening variable was never the intelligence. It was the aim. I wrote the full story: the one fear about AI everyone gets wrong, and the one already here.

Casper

91,587 次观看 • 18 天前

THE GUY WHO BUILT GIT GAVE A FULL LECTURE AT GOOGLE BECAUSE 99% OF DEVELOPERS USE IT WRONG 70 minutes of pure firepower from Linus Torvalds himself - the man who wrote both Linux and Git from scratch. -> The moment you watch it, you realize why "I'll just figure out merge conflicts on the job" is the dumbest sentence in modern software engineering. He spends the first 10 minutes calling out every other version control system in existence and he's not joking. He literally tells Google engineers using Perforce to find a new tool. Git isn't a "nice-to-have" anymore -> it's the operating system of every codebase you'll ever touch. If the man who built it had to explain it to a room full of Google engineers, you don't get a pass either. Don't forget to bookmark & watch it today.

THE GUY WHO BUILT GIT GAVE A FULL LECTURE AT GOOGLE BECAUSE 99% OF DEVELOPERS USE IT WRONG 70 minutes of pure firepower from Linus Torvalds himself - the man who wrote both Linux and Git from scratch. -> The moment you watch it, you realize why "I'll just figure out merge conflicts on the job" is the dumbest sentence in modern software engineering. He spends the first 10 minutes calling out every other version control system in existence and he's not joking. He literally tells Google engineers using Perforce to find a new tool. Git isn't a "nice-to-have" anymore -> it's the operating system of every codebase you'll ever touch. If the man who built it had to explain it to a room full of Google engineers, you don't get a pass either. Don't forget to bookmark & watch it today.

slash1s

214,200 次观看 • 2 个月前