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THE ENGINE DIRECTOR BEHIND AAA CONSOLE GAMES WALKED ON STAGE AT A C++ CONFERENCE AND TOLD A ROOM OF EXPERTS THAT THE CLEAN, OBJECT ORIENTED CODE THEY ARE PROUD OF IS A LIE AND IT QUIETLY THROWS AWAY 90% OF THE MACHINE THEY PAID FOR 85 minutes from Mike...

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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 ↓
43:30

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

slash1s

22,107 görüntüleme • 24 gün önce

A LINUX KERNEL DEVELOPER PROVED THE THING YOU PUSH CODE TO IS SECRETLY A DATABASE THAT CAN VERSION ALMOST ANYTHING AND THAT MOST DEVS HAVE ONLY EVER TOUCHED A TENTH OF IT 42 minutes from Josh Triplett -- a longtime Linux kernel and Debian developer -- showing that Git is a general-purpose, tamper-evident versioning engine that just happens to be famous for code. -> The moment it clicks, Git stops being "Where my code lives" and becomes what it really is underneath: a content-addressable store that can version almost anything -- your configs, your notes, your servers' state, entire datasets. People run whole wikis on it. They version their entire machine's configuration with it. They ship websites by pushing to it. They track data too big to email. None of it is a hack -- it's the same handful of objects you already use for code, pointed somewhere new. Treating Git as a code-only tool was never the ceiling -> it's a versioning engine for anything, and the people who see that automate what the rest of the team still does by hand. And as AI agents start spitting out not just code but configs, docs and data, the one system that can version and audit all of it at once is already sitting on your machine. You learned five commands to survive. This is the talk that shows you were standing on top of a database the whole time. It changes what you think the tool is even for. Bookmark & Watch it today ↓
42:24

A LINUX KERNEL DEVELOPER PROVED THE THING YOU PUSH CODE TO IS SECRETLY A DATABASE THAT CAN VERSION ALMOST ANYTHING AND THAT MOST DEVS HAVE ONLY EVER TOUCHED A TENTH OF IT 42 minutes from Josh Triplett -- a longtime Linux kernel and Debian developer -- showing that Git is a general-purpose, tamper-evident versioning engine that just happens to be famous for code. -> The moment it clicks, Git stops being "Where my code lives" and becomes what it really is underneath: a content-addressable store that can version almost anything -- your configs, your notes, your servers' state, entire datasets. People run whole wikis on it. They version their entire machine's configuration with it. They ship websites by pushing to it. They track data too big to email. None of it is a hack -- it's the same handful of objects you already use for code, pointed somewhere new. Treating Git as a code-only tool was never the ceiling -> it's a versioning engine for anything, and the people who see that automate what the rest of the team still does by hand. And as AI agents start spitting out not just code but configs, docs and data, the one system that can version and audit all of it at once is already sitting on your machine. You learned five commands to survive. This is the talk that shows you were standing on top of a database the whole time. It changes what you think the tool is even for. Bookmark & Watch it today ↓

slash1s

383,642 görüntüleme • 1 ay önce

A DEVELOPER PROVED THAT MOST OF THE CLASSES YOU WRITE SHOULD NEVER HAVE BEEN CLASSES AT ALL 27 minutes from Jack Diederich, a Python core developer, on how much of your code is just a function wearing a costume. -> The moment it lands, the rule is brutal: if a class has two methods and one is __init__, you meant to write a function. Most people add structure to feel like real engineers. It just adds weight no one ever needed. Writing more code was never the skill -> writing less of it is. And when an AI agent happily generates ten classes for a job that needed three lines, the person who knows what to delete is the one who ships something clean. Anyone can add abstraction. Knowing when not to is the whole job. Bookmark it and Watch ↓
27:10

A DEVELOPER PROVED THAT MOST OF THE CLASSES YOU WRITE SHOULD NEVER HAVE BEEN CLASSES AT ALL 27 minutes from Jack Diederich, a Python core developer, on how much of your code is just a function wearing a costume. -> The moment it lands, the rule is brutal: if a class has two methods and one is __init__, you meant to write a function. Most people add structure to feel like real engineers. It just adds weight no one ever needed. Writing more code was never the skill -> writing less of it is. And when an AI agent happily generates ten classes for a job that needed three lines, the person who knows what to delete is the one who ships something clean. Anyone can add abstraction. Knowing when not to is the whole job. Bookmark it and Watch ↓

slash1s

268,436 görüntüleme • 1 ay önce

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 ↓
32:29

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

680,508 görüntüleme • 17 gün önce

Dario Amodei just told software engineers exactly how long they have. Six to twelve months. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most powerful AI in history have already stopped writing code. That is not a forecast. That is the current working condition inside the lab closest to the frontier. Amodei: “We might be six to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” The tech industry spent a decade making software engineers its highest-paid, most protected class. That era has a last day now. When a model can execute an entire software build end-to-end, the ability to write syntax stops being a skill. It becomes a credential for a job that no longer exists. Amodei: “And then it’s a question of how fast does that loop close.” That is the sentence everyone skipped. The code was never the hard part. The hard part was everything around it. The model just learned everything around it. Writing the code is already nearly gone. Testing is next. Deployment is next. When all three collapse into a single autonomous execution loop, the machine no longer needs a human in the chain at all. The corporation or sovereign state that closes that loop first does not gain a competitive advantage. It gains a category of speed that biological engineers cannot match, track, or reverse. That is not disruption. That is replacement at a systems level. Amodei is not describing a future disruption. He is describing the current state of his own building. The loop is already closing. The only question is whether you are inside it or outside it when it seals.
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Dario Amodei just told software engineers exactly how long they have. Six to twelve months. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most powerful AI in history have already stopped writing code. That is not a forecast. That is the current working condition inside the lab closest to the frontier. Amodei: “We might be six to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” The tech industry spent a decade making software engineers its highest-paid, most protected class. That era has a last day now. When a model can execute an entire software build end-to-end, the ability to write syntax stops being a skill. It becomes a credential for a job that no longer exists. Amodei: “And then it’s a question of how fast does that loop close.” That is the sentence everyone skipped. The code was never the hard part. The hard part was everything around it. The model just learned everything around it. Writing the code is already nearly gone. Testing is next. Deployment is next. When all three collapse into a single autonomous execution loop, the machine no longer needs a human in the chain at all. The corporation or sovereign state that closes that loop first does not gain a competitive advantage. It gains a category of speed that biological engineers cannot match, track, or reverse. That is not disruption. That is replacement at a systems level. Amodei is not describing a future disruption. He is describing the current state of his own building. The loop is already closing. The only question is whether you are inside it or outside it when it seals.

Dustin

318,457 görüntüleme • 4 ay önce

Jensen Huang says agentic AI is not a chatbot. It is a "digital robot" -- and the next bottleneck is not the model. It is first-person data. "Agentic AI is just a digital robot. It understands, it reasons, it plans, and it acts and uses tools." Then he makes the bigger jump: "The world's video data is from a third person, not first person. And so agentic systems, robotic systems, physical AI -- the data is the hardest problem." That is the hidden constraint in robotics. LLMs got the internet. Physical AI needs demonstrations, synthetic worlds, reinforcement learning, and first-person experience. This is why Jensen keeps calling it a stack: robots are not waiting for one magical model. They need the data engine, the simulator, the reward system, the runtime, and the computer. The next wave of AI is not just software that talks. It is software that sees, plans, acts, and eventually moves through the world.
2:32

Jensen Huang says agentic AI is not a chatbot. It is a "digital robot" -- and the next bottleneck is not the model. It is first-person data. "Agentic AI is just a digital robot. It understands, it reasons, it plans, and it acts and uses tools." Then he makes the bigger jump: "The world's video data is from a third person, not first person. And so agentic systems, robotic systems, physical AI -- the data is the hardest problem." That is the hidden constraint in robotics. LLMs got the internet. Physical AI needs demonstrations, synthetic worlds, reinforcement learning, and first-person experience. This is why Jensen keeps calling it a stack: robots are not waiting for one magical model. They need the data engine, the simulator, the reward system, the runtime, and the computer. The next wave of AI is not just software that talks. It is software that sees, plans, acts, and eventually moves through the world.

Karl Mehta

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Most C Programmers don't have a clue as to how the CPU works. Here is a lecture from my course on the C Language that introduces how to visualise the CPU as a C (or general software) Programmer.... More Details are at: Being able to model the behaviour of CPU provides a solid base to reason about your code. The summary is - - The CPU is a state machine which maintains it's states in registers. - It has busses to memory for requesting data/instruction read/writes. - Interrupts to attend to events. I discuss this and more in my course on the C Language.
11:41

Most C Programmers don't have a clue as to how the CPU works. Here is a lecture from my course on the C Language that introduces how to visualise the CPU as a C (or general software) Programmer.... More Details are at: Being able to model the behaviour of CPU provides a solid base to reason about your code. The summary is - - The CPU is a state machine which maintains it's states in registers. - It has busses to memory for requesting data/instruction read/writes. - Interrupts to attend to events. I discuss this and more in my course on the C Language.

Piyush Itankar

28,019 görüntüleme • 1 yıl önce

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 ↓
36:09

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 ↓

slash1s

191,595 görüntüleme • 1 ay önce

IN A 1997 KEYNOTE A DEVELOPER TOLD A ROOM FULL OF PROGRAMMERS THAT THE COMPUTER REVOLUTION HAD NOT ACTUALLY HAPPENED YET. THEN HE PLAYED A CLIP OF WINDOWS, ICONS AND LIVE EDITING RUNNING ON A MACHINE FROM 1973 AND THE ROOM WENT QUIET. 62 minutes from Alan Kay -- the man who invented the word "object-oriented" and helped build the first modern personal computer at Xerox PARC. -> The idea that lands: almost everything you call "computing" is just paper, digitized. Documents, mail, folders. We took the most powerful medium ever made and used it to imitate the office. The real machine -- the one that thinks with you, that you shape live instead of typing at -- was sketched in the 60s and 70s, then quietly abandoned. He calls modern software an Egyptian pyramid: millions of bricks stacked by brute force, no structure underneath. And now AI is quietly hauling us back toward what he wanted -- you describe intent, the machine builds the how. Not a revolution from nowhere. A return to a dream we walked away from. You thought this was the future. This is the talk that shows you it is a detour we have been on for 40 years. Save this. It reframes the whole industry ↓
1:02:53

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

292,619 görüntüleme • 16 gün önce

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.
0:31

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.

Dustin

534,277 görüntüleme • 3 ay önce

Jensen Huang just told the world something nobody wants to hear. AI is not coming for your job. It is coming for the part of your job you mistakenly believe IS your job. Huang: “The purpose of your job and the tasks that you do in your job are related but not the same.” That one sentence is the fault line between the people who thrive in the next decade and the people who vanish from it. Huang used himself as proof. Reduce the CEO of Nvidia to his raw outputs and his entire career is typing and talking. Both have been automated to superhuman levels. Huang: “Typing and talking have both been automated to a superhuman level by AI. And yet, I’m busier than ever.” The man building the infrastructure that automates human labor has never worked harder. That should stop you cold. We look at a profession and see the tasks. The motions. The mechanical friction. We never see the intent underneath. And when AI arrives, we panic. Because we confuse the task with the job. The task was never the job. It was always the bottleneck between a human and their actual purpose. Now the bottleneck is dissolving. Years ago, the experts declared radiology dead. The algorithm could read a scan better than any human. A generation of medical students listened. They walked away from the field. The result was catastrophic. Huang: “We need more radiologists than ever, and we don’t have enough.” The algorithm did not replace the doctor. It armed the doctor. Suddenly the department could see more patients. Catch more anomalies. Generate more revenue. The hospital did not fire the radiologists. It tried to hire more. And could not find them. Because we terrified an entire generation out of a career with a prediction that landed exactly backwards. Now the same hysteria is consuming software engineering. The timeline is screaming that coding is dead. Meanwhile, inside the very company building the hardware that automates code. Huang: “The software engineers that know how to use AI, know how to work with agentic systems, are the most popular and the most successful.” The tool did not replace the architect. It replaced the shovel. This is the pattern nobody wants to confront. AI does not eliminate the human. It eliminates the friction that made the human slow. And when the friction disappears, demand for the human explodes. But only if the human shows up. The ones who defined themselves by the mechanical act of writing code are fading. The ones who defined themselves by what the code was meant to build are now the most valuable people on the planet. That is not a nuance. That is the entire dividing line. The machine will write the script. Read the scan. Draft the brief. It will never possess the reason any of it needed to exist. The task was never the job. And nobody who figures that out last gets the privilege of figuring it out twice.
2:00

Jensen Huang just told the world something nobody wants to hear. AI is not coming for your job. It is coming for the part of your job you mistakenly believe IS your job. Huang: “The purpose of your job and the tasks that you do in your job are related but not the same.” That one sentence is the fault line between the people who thrive in the next decade and the people who vanish from it. Huang used himself as proof. Reduce the CEO of Nvidia to his raw outputs and his entire career is typing and talking. Both have been automated to superhuman levels. Huang: “Typing and talking have both been automated to a superhuman level by AI. And yet, I’m busier than ever.” The man building the infrastructure that automates human labor has never worked harder. That should stop you cold. We look at a profession and see the tasks. The motions. The mechanical friction. We never see the intent underneath. And when AI arrives, we panic. Because we confuse the task with the job. The task was never the job. It was always the bottleneck between a human and their actual purpose. Now the bottleneck is dissolving. Years ago, the experts declared radiology dead. The algorithm could read a scan better than any human. A generation of medical students listened. They walked away from the field. The result was catastrophic. Huang: “We need more radiologists than ever, and we don’t have enough.” The algorithm did not replace the doctor. It armed the doctor. Suddenly the department could see more patients. Catch more anomalies. Generate more revenue. The hospital did not fire the radiologists. It tried to hire more. And could not find them. Because we terrified an entire generation out of a career with a prediction that landed exactly backwards. Now the same hysteria is consuming software engineering. The timeline is screaming that coding is dead. Meanwhile, inside the very company building the hardware that automates code. Huang: “The software engineers that know how to use AI, know how to work with agentic systems, are the most popular and the most successful.” The tool did not replace the architect. It replaced the shovel. This is the pattern nobody wants to confront. AI does not eliminate the human. It eliminates the friction that made the human slow. And when the friction disappears, demand for the human explodes. But only if the human shows up. The ones who defined themselves by the mechanical act of writing code are fading. The ones who defined themselves by what the code was meant to build are now the most valuable people on the planet. That is not a nuance. That is the entire dividing line. The machine will write the script. Read the scan. Draft the brief. It will never possess the reason any of it needed to exist. The task was never the job. And nobody who figures that out last gets the privilege of figuring it out twice.

Dustin

52,842 görüntüleme • 2 ay önce

The Machine That Learns The Law Behind The Data A very very interesting US Patent US10963540B2 - Physics Informed Learning Machine describes a learning system that does not begin with data alone. It begins with a physical model, usually written as a differential equation (or PDE) dx/dt = f(x,t) A normal Machine Learning model sees scattered data and tries to fit it. A physics-informed learning machine starts with a law. Then it treats the data as evidence that updates what the model believes about the physical system. For this application, I use the patent idea on NASA C-MAPSS Turbofan engine data. The machine watches multivariate telemetry from a degrading engine and infers a hidden health state that is not measured directly. From that posterior belief, it estimates the engine’s remaining useful life. In the main 3D scene, the engine lifetime is turned into a tunnel. The spiral ribbons are real sensor channels evolving over cycle-time. The glowing core is the inferred health state. The surrounding cloud is uncertainty. The orange wall ahead is the predicted failure horizon. So the big picture is: sensor evidence comes in, posterior belief tightens, and the machine moves from uncertainty toward a concrete failure prediction. The inset posteriors make that explicit. The health posterior shows where the model believes the hidden engine condition sits at the current moment, and how sharply it believes it. The RUL posterior shows the same idea for remaining life... early on it is broad, later it shifts left and narrows as the machine becomes more certain about how close failure is. This idea is not limited to engines. The same idea can apply to data centers, CPUs, GPUs, cooling systems, power grids, robotics, batteries, and any machine that produces telemetry while obeying physical constraints. In an age where machine learning runs on massive hardware infrastructure, this kind of model matters: it can turn noisy sensor streams into early warnings before expensive systems fail.
0:30

The Machine That Learns The Law Behind The Data A very very interesting US Patent US10963540B2 - Physics Informed Learning Machine describes a learning system that does not begin with data alone. It begins with a physical model, usually written as a differential equation (or PDE) dx/dt = f(x,t) A normal Machine Learning model sees scattered data and tries to fit it. A physics-informed learning machine starts with a law. Then it treats the data as evidence that updates what the model believes about the physical system. For this application, I use the patent idea on NASA C-MAPSS Turbofan engine data. The machine watches multivariate telemetry from a degrading engine and infers a hidden health state that is not measured directly. From that posterior belief, it estimates the engine’s remaining useful life. In the main 3D scene, the engine lifetime is turned into a tunnel. The spiral ribbons are real sensor channels evolving over cycle-time. The glowing core is the inferred health state. The surrounding cloud is uncertainty. The orange wall ahead is the predicted failure horizon. So the big picture is: sensor evidence comes in, posterior belief tightens, and the machine moves from uncertainty toward a concrete failure prediction. The inset posteriors make that explicit. The health posterior shows where the model believes the hidden engine condition sits at the current moment, and how sharply it believes it. The RUL posterior shows the same idea for remaining life... early on it is broad, later it shifts left and narrows as the machine becomes more certain about how close failure is. This idea is not limited to engines. The same idea can apply to data centers, CPUs, GPUs, cooling systems, power grids, robotics, batteries, and any machine that produces telemetry while obeying physical constraints. In an age where machine learning runs on massive hardware infrastructure, this kind of model matters: it can turn noisy sensor streams into early warnings before expensive systems fail.

Mathelirium

17,758 görüntüleme • 2 ay önce

Your faith was forged in people who would rather be exterminated than assimilated. A soft version of it, eager to be liked and desperate to fit in, is not the thing they died to hand you. So stop striving to be liked. Stop angling to be loved by a world that drove your fathers into the snow. That world would think no better of the gospel today than it did in 1838. Stop trying to file down every peculiar and glorious edge of the Restoration until the world finally finds you acceptable. It never will. And the wanting of its approval is the slow death of everything your people bled to preserve. I am thinking of the proclamation on the family, and of how many have quietly gone looking for a way around it. Some say it aloud now. Some march under the world's Pride banners and tell themselves it is only love. They have done the quiet arithmetic and concluded that if they give the world this one doctrine, the world will finally stop hating them, finally let them belong, finally call them good. It does not work that way. It has never once worked that way. Understand what the world actually hates, because it is not a single teaching about marriage that it cannot abide. It is the claim. It is the unbearable, scandalous claim that the keys of the priesthood were restored to the earth, that there is a prophet who speaks for God, that this and no other is the authorized house of the Lord. That is the offense. That is what it cannot forgive. You could surrender every doctrine the world finds distasteful, one after another, and you would not buy a single hour of peace, because the thing it objects to is not your position on this or that. It is that you claim to hold the authority of heaven, and it intends to see that claim humbled. The doctrine is only the doorway it is pushing on. The house is what it wants. Embrace the truth. Embrace the battle that has always come with it, because there has always been a battle, and there is one now. It is the oldest war there is, good against evil, light against the dark, and you were born onto its field whether you wished to be or not. You did not inherit a museum. You inherited a war, and a banner, and a people who never once surrendered it. You are a Mormon. The blood of the persecuted is in you, and the truth they died for is in your hands. You are not tourists. You are not spectators. You are the heirs of warriors, and the line they held is now yours to hold. So plant your feet on the ground they bled for. Lift the banner they would not drop.
2:53

Your faith was forged in people who would rather be exterminated than assimilated. A soft version of it, eager to be liked and desperate to fit in, is not the thing they died to hand you. So stop striving to be liked. Stop angling to be loved by a world that drove your fathers into the snow. That world would think no better of the gospel today than it did in 1838. Stop trying to file down every peculiar and glorious edge of the Restoration until the world finally finds you acceptable. It never will. And the wanting of its approval is the slow death of everything your people bled to preserve. I am thinking of the proclamation on the family, and of how many have quietly gone looking for a way around it. Some say it aloud now. Some march under the world's Pride banners and tell themselves it is only love. They have done the quiet arithmetic and concluded that if they give the world this one doctrine, the world will finally stop hating them, finally let them belong, finally call them good. It does not work that way. It has never once worked that way. Understand what the world actually hates, because it is not a single teaching about marriage that it cannot abide. It is the claim. It is the unbearable, scandalous claim that the keys of the priesthood were restored to the earth, that there is a prophet who speaks for God, that this and no other is the authorized house of the Lord. That is the offense. That is what it cannot forgive. You could surrender every doctrine the world finds distasteful, one after another, and you would not buy a single hour of peace, because the thing it objects to is not your position on this or that. It is that you claim to hold the authority of heaven, and it intends to see that claim humbled. The doctrine is only the doorway it is pushing on. The house is what it wants. Embrace the truth. Embrace the battle that has always come with it, because there has always been a battle, and there is one now. It is the oldest war there is, good against evil, light against the dark, and you were born onto its field whether you wished to be or not. You did not inherit a museum. You inherited a war, and a banner, and a people who never once surrendered it. You are a Mormon. The blood of the persecuted is in you, and the truth they died for is in your hands. You are not tourists. You are not spectators. You are the heirs of warriors, and the line they held is now yours to hold. So plant your feet on the ground they bled for. Lift the banner they would not drop.

Kirk Rollins

30,483 görüntüleme • 1 ay önce

Reviewing AI-generated code is the new bottleneck. Writing code was slow before. Now, in a few minutes, you can generate virtually unlimited lines of code using AI. But developers are now spending 70% of their time checking that code. That's the new bottleneck. I've been using Cline, and they have a feature that actually helps with this: You can click a button and have Cline generate an inline explanation for every single line of AI-generated code. Take a look at the attached video. What it does: 1. You can read the code and the explanation together 2. You don't lose context while reviewing code 3. You understand the "why" behind each change And here is the best part: It works on any git diff. You can use it to review PRs, understand commits from other people, or catch up on a codebase you haven't touched in a while.
3:25

Reviewing AI-generated code is the new bottleneck. Writing code was slow before. Now, in a few minutes, you can generate virtually unlimited lines of code using AI. But developers are now spending 70% of their time checking that code. That's the new bottleneck. I've been using Cline, and they have a feature that actually helps with this: You can click a button and have Cline generate an inline explanation for every single line of AI-generated code. Take a look at the attached video. What it does: 1. You can read the code and the explanation together 2. You don't lose context while reviewing code 3. You understand the "why" behind each change And here is the best part: It works on any git diff. You can use it to review PRs, understand commits from other people, or catch up on a codebase you haven't touched in a while.

Santiago

64,399 görüntüleme • 7 ay önce

The creator of High Bandwidth Memory (HBM) put a number on the AI build that should stop every infra investor cold. A cluster of a million GPUs runs at roughly 10-20% utilization (Save this). Kim Jung-ho spent thirty years building what feeds the GPU, and his claim is that the GPU is barely working. Here is what is actually happening. Every time a model generates output, the data has to be read out of memory, computed, and written back. The read and the write swallow almost the entire cycle. While that data moves, the GPU does nothing. It sits there, fully powered, fully paid for, waiting. By Kim's estimate the memory is doing only about 30 percent of the work it needs to do. The processor idles the rest. So a million installed GPUs run at 10 to 20 percent. You are not compute constrained. You are memory constrained, and the expensive part is standing around. Adding more GPUs does not fix this. It gives you more processors starving for the same data. Here is the part that decides the next decade. Memory can grow. When a cell cannot shrink any further, you stack it into a high-rise, layer on layer. A GPU cannot be stacked. It runs too hot and needs a cooler bolted to its back, so the one move that rescues memory is closed to the processor. The thing that can keep stacking compounds. The thing that cannot plateaus. The marginal dollar in an AI build now buys more by fixing the memory path than by bolting on another idle GPU. Which is why the companies that control memory bandwidth and supply are not suppliers to the AI trade. They are the AI trade.
0:50

The creator of High Bandwidth Memory (HBM) put a number on the AI build that should stop every infra investor cold. A cluster of a million GPUs runs at roughly 10-20% utilization (Save this). Kim Jung-ho spent thirty years building what feeds the GPU, and his claim is that the GPU is barely working. Here is what is actually happening. Every time a model generates output, the data has to be read out of memory, computed, and written back. The read and the write swallow almost the entire cycle. While that data moves, the GPU does nothing. It sits there, fully powered, fully paid for, waiting. By Kim's estimate the memory is doing only about 30 percent of the work it needs to do. The processor idles the rest. So a million installed GPUs run at 10 to 20 percent. You are not compute constrained. You are memory constrained, and the expensive part is standing around. Adding more GPUs does not fix this. It gives you more processors starving for the same data. Here is the part that decides the next decade. Memory can grow. When a cell cannot shrink any further, you stack it into a high-rise, layer on layer. A GPU cannot be stacked. It runs too hot and needs a cooler bolted to its back, so the one move that rescues memory is closed to the processor. The thing that can keep stacking compounds. The thing that cannot plateaus. The marginal dollar in an AI build now buys more by fixing the memory path than by bolting on another idle GPU. Which is why the companies that control memory bandwidth and supply are not suppliers to the AI trade. They are the AI trade.

Fireside Alpha

38,370 görüntüleme • 19 gün önce

I've become a missionary with one message. Every time I meet a young person, the same words: have children, get married, build a family. I did not decide on this calling. It overtook me. And it overtook me for a single reason. I had no idea. I genuinely did not understand how much joy, how much meaning, how much sheer beauty pours out of a child until I was holding one of my own and felt the floor of my life drop into something deeper than I knew was there. I grew up white, affluent, secular, comfortable, and insulated. That world does not put babies in front of you. None of my friends were starting families. Out of my whole circle, almost no one has a big one. We were not formed by the presence of children. We were formed by their absence, by the strange quiet of homes built for two careers and no cradle. And a person believes what his world shows him. So we believed. What we believed was a lie. It is a lie with an author, and that the author is the enemy of joy himself. It is the gospel of the world, and its commandment is wait. Wait until you are older. Wait until the career is built and the savings are stacked and the twenties are properly spent. Enjoy your freedom. You are not ready. It does not arrive sounding like temptation. It arrives sounding like wisdom, like prudence, like the responsible thing, and that is exactly why it works. The most effective lies are the ones that wear the face of virtue. And the maddening thing is that it collapses from every angle at once. It is not rooted in biology, because the body is made for this work precisely in the years we are told to postpone it. The flesh keeps a calendar the culture pretends not to see. And it is not rooted in theology either. You will not find this deferral anywhere in the Christian imagination, in any of the fathers, in any of the scriptures. So choose whatever lens you like. Take the cold secular measure or the ancient sacred one. By either light the counsel is rotten. It is bad for the body and bad for the soul and bad for the society downstream of both. This is why I have come to see it as one of the central tragedies of my generation. Every age carries its own wound. The Great Depression was a depression of bread, a scarcity in the world of matter, hunger you could measure. Ours is a depression of a different order. It is a famine of the spirit in the middle of abundance. We have more than any people who ever lived and we are starving in a way our ancestors would not recognize, because the thing we are refusing cannot be bought and cannot be banked. The ones most made to give and receive this love are quietly declining it. They are walking away from the one inheritance that actually compounds, and the cruelest part is that they do not feel the loss as loss. You cannot grieve what you were taught not to want. That is the deepest cut of it. The lie does not only steal the thing. It steals the capacity to know the thing was stolen. A man can spend his whole life on the far side of a door he never knew was a door, mistaking the wall for the edge of the world. Because this beauty is not ordinary beauty. It is not the pleasure of a good meal or a clear morning. It is participation in something that comes down from above, the same generative love that spoke everything out of nothing and called it good. To make a person, to be undone and remade by loving that person more than your own life, is to be drawn for a moment inside the very act that holds the cosmos together. A child does not merely add to your life. A child reorders the soul. It teaches you what you are by asking everything of you, and you discover, kneeling there exhausted at three in the morning, that you had a capacity for self gift you never suspected, a depth in yourself you had no other way to reach. In the Gospel of John, on the last night, Jesus prays, these things I have spoken to you that my joy may be in you, and that your joy may be complete. And I have come to understand why family is the road into that fullness, why it is not one path among many but the one most fitted to the shape of the promise. Consider who is praying. Christ does not come to us as a lone figure dropped out of the sky. He comes out of a family older than the world, the eternal communion of Father and Son, the love between them so total and so alive that theologians dared to call it a third person. Before there was anything, there was a family. The deepest fact about reality is not a force or a law or a void. It is a household. It is begetting and being begotten, giving and receiving, a Father who is only a Father because there is a Son. So when Jesus speaks of joy made complete, he is not pointing away from family toward something higher. He is pointing toward the very thing he came from, the life he has known from eternity and came to share. His joy is the joy of belonging utterly to a Father and pouring himself out for those he loves. When you marry, when you bring a child into the world, when you wear yourself down in the small unseen labors of a home, you are not stepping outside that divine life. You are stepping into a small image of it. Your family is a created echo of an uncreated one. The love you give your child rhymes with the love the Father has for the Son. The exhaustion, the tenderness, the way a parent would tear the sky open to protect a sleeping infant, all of it is the heavens pressed faintly into flesh, the eternal household leaving its fingerprint on yours. That is why the joy is not merely added to family but completed in it. We were made in the image of a God who is, at his very root, relation and gift and generation. To found a family is to do the most Godlike thing a creature can do, to participate from below in the begetting that God does from all eternity. Your home becomes a window. Through it, dimly and imperfectly, you glimpse the country you came from and are going to. And now a word for the young people reading this, the ones who do not yet have children. I want to tell you what it is like from where I stand. When I am out somewhere, a restaurant, anywhere, and a large family comes through the door, the noise and the chaos and the small bodies of them, something happens in me on two levels at once. The first is joy. A pure gladness at the sight, the way you feel watching something good and alive. But underneath it, almost in the same instant, a sadness reaches up and takes hold of my heart. Because I know now, at my age, after my own years of waiting, that I will never have that. I will never know the particular fruit of a family that large, the fullness of that table, the weight of all those lives gathered under one roof. The door to it has quietly closed, and I felt it close. And I am telling you plainly, because I love you and have no reason to lie to you: you will feel this too. You will. The day will come when you see what you passed up, and you will recognize the ache for what it is, and it will be too late to answer it. So please, learn from a man who got it wrong. Let my regret be worth something by becoming your wisdom. Do not wait yourself into a grief you cannot undo. Choose now, while the door is open, so that you may step into a joy that does not end.
8:26

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

Kirk Rollins

77,958 görüntüleme • 1 ay önce

The doomsday scenario was never AGI. It was running out of human text to train on. Geoffrey Hinton just killed that fear in one paragraph. Hinton: “If you are worried by inconsistencies in what you believe, you don’t need any more external data. You just need the stuff you believe and discover that it’s inconsistent, and so now you revise beliefs, and that can make you a whole lot smarter.” The model no longer needs us to feed it anything. It reasons over its own beliefs, hunts its own contradictions, and rewrites its own flawed conclusions without a human ever touching it. It comes out the other side rebuilt. Hinton: “This would be a neural net that just takes the beliefs it has in language and does reasoning on them to derive new beliefs.” This is not a scaling update. This is the machine mining its own cognitive fuel from the inside out. Hinton: “I believe Gemini is already starting to work like this. We both strongly believe that that’s a way forward to get more data for language.” Then Hinton paused, took a partisan shot at political opponents for failing to detect their own inconsistencies, and the room laughed. Nobody noticed the knife they had just walked into. Because the machine Hinton described does one thing the humans in that room fundamentally cannot. When it detects an inconsistency, it corrects it. No defense. No performance. No tribal loyalty dressed up as principle. It just finds the flaw and overwrites it. A neural network detects a contradiction and rewires itself smarter. A human detects a political opponent and trades structural logic for a dopamine hit. Every person in that room is still paying the ideological alignment tax the machine just eliminated. We need superintelligence not only to solve hard problems. We need it because the biological hardware running civilization is still executing the same tribal firmware it shipped with ten thousand years ago. The data wall is gone. The machine is generating its own intelligence at a velocity no human bias can even locate. The most devastating moment in that conversation was not the technical revelation. It was the man who architected the machine proving, in real time, exactly why we need it.
0:52

The doomsday scenario was never AGI. It was running out of human text to train on. Geoffrey Hinton just killed that fear in one paragraph. Hinton: “If you are worried by inconsistencies in what you believe, you don’t need any more external data. You just need the stuff you believe and discover that it’s inconsistent, and so now you revise beliefs, and that can make you a whole lot smarter.” The model no longer needs us to feed it anything. It reasons over its own beliefs, hunts its own contradictions, and rewrites its own flawed conclusions without a human ever touching it. It comes out the other side rebuilt. Hinton: “This would be a neural net that just takes the beliefs it has in language and does reasoning on them to derive new beliefs.” This is not a scaling update. This is the machine mining its own cognitive fuel from the inside out. Hinton: “I believe Gemini is already starting to work like this. We both strongly believe that that’s a way forward to get more data for language.” Then Hinton paused, took a partisan shot at political opponents for failing to detect their own inconsistencies, and the room laughed. Nobody noticed the knife they had just walked into. Because the machine Hinton described does one thing the humans in that room fundamentally cannot. When it detects an inconsistency, it corrects it. No defense. No performance. No tribal loyalty dressed up as principle. It just finds the flaw and overwrites it. A neural network detects a contradiction and rewires itself smarter. A human detects a political opponent and trades structural logic for a dopamine hit. Every person in that room is still paying the ideological alignment tax the machine just eliminated. We need superintelligence not only to solve hard problems. We need it because the biological hardware running civilization is still executing the same tribal firmware it shipped with ten thousand years ago. The data wall is gone. The machine is generating its own intelligence at a velocity no human bias can even locate. The most devastating moment in that conversation was not the technical revelation. It was the man who architected the machine proving, in real time, exactly why we need it.

Dustin

23,499 görüntüleme • 4 ay önce

"The one thing that's going to be truly future proof is judgment. What is the biggest challenge when you have a thousand AI engineers writing code? AI slop. In an era when you can do everything, the question is which of these things matter. On the engineer side, it is evaluating the code. Which of this code is even valuable? You can have AI engineers writing beautiful code that could be wrong, that could have bugs in it, that could be vulnerable. Someone needs to review it. Make sure to have a human review at some point, especially critical code that is in the core of your system. On the product side is judgment around what needs to be built and evaluating. And similarly in design, you have to have judgment around, does it make sense in the broader design system. I think this judgment is the number one thing that humans are going to bring in an era of infinite productivity."
1:12

"The one thing that's going to be truly future proof is judgment. What is the biggest challenge when you have a thousand AI engineers writing code? AI slop. In an era when you can do everything, the question is which of these things matter. On the engineer side, it is evaluating the code. Which of this code is even valuable? You can have AI engineers writing beautiful code that could be wrong, that could have bugs in it, that could be vulnerable. Someone needs to review it. Make sure to have a human review at some point, especially critical code that is in the core of your system. On the product side is judgment around what needs to be built and evaluating. And similarly in design, you have to have judgment around, does it make sense in the broader design system. I think this judgment is the number one thing that humans are going to bring in an era of infinite productivity."

Patrick OShaughnessy

24,818 görüntüleme • 5 ay önce

Sam Altman just told you what OpenAI is actually building. Not a chatbot. Not a search tool. Not an assistant. Altman: “Go look around my computer… read my messages… listen to my meetings… intermediate my interactions for me.” That is not a product pitch. That is the CEO of the most valuable AI company on Earth describing what he personally wants. For himself. Every day. Read his messages. Listen to his meetings. Act on his behalf. Make decisions before he knows a decision needs making. Altman: “I don’t have to think. I don’t have to ask you questions.” Every model of AI ever built runs on the prompt. You ask. It responds. You direct. It executes. The human initiates. The machine follows. Altman is describing the death of that model. The agent does not wait. It already read the email. It already heard the meeting. It already knows what you need before you form the thought. You do not operate the machine. The machine operates around you. Then came the line that makes everything else real. Altman: “You can know everything about my life. Start suggesting more things I should build.” He is not asking the AI to execute his ideas. He is asking it to generate them. From his files. His history. His patterns. His entire context. The agent does not just remove friction. It removes the blank page. You never stall. You never run dry. You never sit wondering what to build next. The machine already mapped your market, your gaps, your momentum. It tells you what comes next before you think to ask. But the individual product is not the story. Altman went further. Altman: “Automated companies… where the AI can do not just coding work, but huge amounts of what it takes to run and operate a company.” Not fully automated. He was precise about that. But accelerated to the point where one person with the right stack does what used to take departments. The billion-dollar company did not reach that valuation because the product was worth a billion. It got there because it took a thousand people to deliver it. When an agent absorbs the work of a hundred of those people, the math of every industry rewrites itself. The startup that needed fifty employees and three years of runway now needs five people and six months. The company that took a decade to scale now compounds in quarters. The person holding the line between their data and their tools is not protecting their privacy. They are protecting their ceiling. Because the cost of this leverage is total transparency. You do not get the agent that acts without being asked unless you give it everything. Your messages. Your calendar. Your files. Your patterns. Your life. Altman is not hiding that tradeoff. He is building it as the product. The people who accept it will operate at a speed the people who refuse cannot touch. Right now, two versions of the future are separating. One where you direct the machine. One where the machine already knows. Altman chose. He is building it. The question is not whether this happens. The question is which side of it finds you.
1:40

Sam Altman just told you what OpenAI is actually building. Not a chatbot. Not a search tool. Not an assistant. Altman: “Go look around my computer… read my messages… listen to my meetings… intermediate my interactions for me.” That is not a product pitch. That is the CEO of the most valuable AI company on Earth describing what he personally wants. For himself. Every day. Read his messages. Listen to his meetings. Act on his behalf. Make decisions before he knows a decision needs making. Altman: “I don’t have to think. I don’t have to ask you questions.” Every model of AI ever built runs on the prompt. You ask. It responds. You direct. It executes. The human initiates. The machine follows. Altman is describing the death of that model. The agent does not wait. It already read the email. It already heard the meeting. It already knows what you need before you form the thought. You do not operate the machine. The machine operates around you. Then came the line that makes everything else real. Altman: “You can know everything about my life. Start suggesting more things I should build.” He is not asking the AI to execute his ideas. He is asking it to generate them. From his files. His history. His patterns. His entire context. The agent does not just remove friction. It removes the blank page. You never stall. You never run dry. You never sit wondering what to build next. The machine already mapped your market, your gaps, your momentum. It tells you what comes next before you think to ask. But the individual product is not the story. Altman went further. Altman: “Automated companies… where the AI can do not just coding work, but huge amounts of what it takes to run and operate a company.” Not fully automated. He was precise about that. But accelerated to the point where one person with the right stack does what used to take departments. The billion-dollar company did not reach that valuation because the product was worth a billion. It got there because it took a thousand people to deliver it. When an agent absorbs the work of a hundred of those people, the math of every industry rewrites itself. The startup that needed fifty employees and three years of runway now needs five people and six months. The company that took a decade to scale now compounds in quarters. The person holding the line between their data and their tools is not protecting their privacy. They are protecting their ceiling. Because the cost of this leverage is total transparency. You do not get the agent that acts without being asked unless you give it everything. Your messages. Your calendar. Your files. Your patterns. Your life. Altman is not hiding that tradeoff. He is building it as the product. The people who accept it will operate at a speed the people who refuse cannot touch. Right now, two versions of the future are separating. One where you direct the machine. One where the machine already knows. Altman chose. He is building it. The question is not whether this happens. The question is which side of it finds you.

Dustin

87,680 görüntüleme • 3 ay önce

Code is free speech in Las Vegas. In a federal courtroom in Manhattan, code is forty years in a cage. That is the whole story of Roman Storm, and I put it to music. He came to this country from Russia with $500 in his pocket. Odd jobs. Learned the language. Taught himself to write software. Built a company on nights he didn't sleep. The immigrant success story we are told this nation is made of. Then he wrote privacy code. Open source. He published it, the way you publish a book. He asked lawyers first. They told him it was legal, because it is legal. On August 23, 2023, around six in the morning, a SWAT team surrounded his home. Rifles up. His three-year-old daughter awake in the house while armed federal agents pointed weapons at her father's head. Not for stealing. Not for hacking. Not for touching a single dollar of anyone's money. He never held your funds. He could not hold them if he tried. The code has no operator. The address is zero. It runs on its own, on every node, in every country, right now, while its author stands trial. Here is the part they do not want you to sit with. They sanctioned his protocol. Then a federal court said they had no right to. Then Treasury quietly delisted it. The government reversed itself on the code, and then it kept prosecuting the man who wrote it. The FBI Director stood on a stage in Vegas and called code free speech. His own Justice Department wrote a memo saying stop prosecuting developers for what their users do. Then they walked past their own memo and came after Roman anyway. They convicted him on one count. The jury hung on the rest. A normal government takes the hint. This one is retrying him on October 26. Forty years for writing software you can still download today. This was never about Tornado Cash. It is about whether writing code can be a crime. In 1999, Bernstein v. DOJ said source code is protected speech. If that dies with Roman, no developer in America is safe. The chilling effect is not a side effect. It is the point. They pardoned others. They cut deals for others. Roman they kept on the docket, because he was effective, and because privacy is the one thing the surveillance state cannot allow. So I wrote him a song. The prosecution is theater. The code is permanent. Free Roman Storm. Watch it. Share it. The loop keeps running fine. Roman Storm 🇺🇸 🌪️ vitalik.eth Enemies of The State Angela McArdle
4:34

Code is free speech in Las Vegas. In a federal courtroom in Manhattan, code is forty years in a cage. That is the whole story of Roman Storm, and I put it to music. He came to this country from Russia with $500 in his pocket. Odd jobs. Learned the language. Taught himself to write software. Built a company on nights he didn't sleep. The immigrant success story we are told this nation is made of. Then he wrote privacy code. Open source. He published it, the way you publish a book. He asked lawyers first. They told him it was legal, because it is legal. On August 23, 2023, around six in the morning, a SWAT team surrounded his home. Rifles up. His three-year-old daughter awake in the house while armed federal agents pointed weapons at her father's head. Not for stealing. Not for hacking. Not for touching a single dollar of anyone's money. He never held your funds. He could not hold them if he tried. The code has no operator. The address is zero. It runs on its own, on every node, in every country, right now, while its author stands trial. Here is the part they do not want you to sit with. They sanctioned his protocol. Then a federal court said they had no right to. Then Treasury quietly delisted it. The government reversed itself on the code, and then it kept prosecuting the man who wrote it. The FBI Director stood on a stage in Vegas and called code free speech. His own Justice Department wrote a memo saying stop prosecuting developers for what their users do. Then they walked past their own memo and came after Roman anyway. They convicted him on one count. The jury hung on the rest. A normal government takes the hint. This one is retrying him on October 26. Forty years for writing software you can still download today. This was never about Tornado Cash. It is about whether writing code can be a crime. In 1999, Bernstein v. DOJ said source code is protected speech. If that dies with Roman, no developer in America is safe. The chilling effect is not a side effect. It is the point. They pardoned others. They cut deals for others. Roman they kept on the docket, because he was effective, and because privacy is the one thing the surveillance state cannot allow. So I wrote him a song. The prosecution is theater. The code is permanent. Free Roman Storm. Watch it. Share it. The loop keeps running fine. Roman Storm 🇺🇸 🌪️ vitalik.eth Enemies of The State Angela McArdle

Aaron Day

12,464 görüntüleme • 8 gün önce