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

Dustin

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Larry Ellison says AI is now writing Oracle's Code. "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. We don't write the procedure, we declare our intent"

Larry Ellison says AI is now writing Oracle's Code. "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. We don't write the procedure, we declare our intent"

Rohan Paul

67,599 Aufrufe • vor 1 Monat

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.

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

52,811 Aufrufe • vor 2 Monaten

Elon Musk was asked what happens to people when the machines no longer need them. He didn’t soften it. Musk: “There will be fewer and fewer jobs that a robot cannot do better. These are not things I wish would happen. They probably will.” Sit with that second sentence. He is not celebrating. He is not selling a vision. He is telling you what he believes is inevitable and admitting he wishes it weren’t. That is not optimism. That is a confession. Most people are still arguing over whether this is real. Whether it’s their job or someone else’s. Whether the timeline is years away or decades. Musk isn’t arguing. He resolved it. And it bothers him. Musk: “I think ultimately we will have to have some kind of universal basic income. I don’t think we’re going to have a choice.” Not a political position. Not a utopian proposal. A concession. We are building something so capable that human labor stops being a required input to the economy. The machine does not need rest. It does not need a salary. It does not call in sick. It does not ask for a raise. And it improves every single month. The jobs that feel safe right now are not safe because they are irreplaceable. They feel safe because the technology hasn’t fully arrived yet. It’s arriving. Musk: “How do people then have meaning? If there’s not a need for your labor, what’s the meaning? Do you feel useless?” He said that is the harder problem. Not the economics. Not the policy. Not how you fund UBI or make it hold. The harder problem is what happens to a person who built their entire identity around being needed. That is most people. You were trained from childhood to believe your value is what you produce. That your worth is what you earn. That rest is something you survive the week to reach, not something you deserve simply by existing. When the machine removes the need for your labor, that belief does not update. It breaks. The people least prepared for that moment are the ones who worked the hardest. The ones who took the most pride in being indispensable. The ones who made work the whole answer. Losing the job is survivable. Losing the reason to get up is not. That is what Musk is actually asking. Not how do we pay people. How do we build a world where people still feel like they matter when the economy no longer needs them. Nobody in power is seriously working on that answer. The machine didn’t wait.

Elon Musk was asked what happens to people when the machines no longer need them. He didn’t soften it. Musk: “There will be fewer and fewer jobs that a robot cannot do better. These are not things I wish would happen. They probably will.” Sit with that second sentence. He is not celebrating. He is not selling a vision. He is telling you what he believes is inevitable and admitting he wishes it weren’t. That is not optimism. That is a confession. Most people are still arguing over whether this is real. Whether it’s their job or someone else’s. Whether the timeline is years away or decades. Musk isn’t arguing. He resolved it. And it bothers him. Musk: “I think ultimately we will have to have some kind of universal basic income. I don’t think we’re going to have a choice.” Not a political position. Not a utopian proposal. A concession. We are building something so capable that human labor stops being a required input to the economy. The machine does not need rest. It does not need a salary. It does not call in sick. It does not ask for a raise. And it improves every single month. The jobs that feel safe right now are not safe because they are irreplaceable. They feel safe because the technology hasn’t fully arrived yet. It’s arriving. Musk: “How do people then have meaning? If there’s not a need for your labor, what’s the meaning? Do you feel useless?” He said that is the harder problem. Not the economics. Not the policy. Not how you fund UBI or make it hold. The harder problem is what happens to a person who built their entire identity around being needed. That is most people. You were trained from childhood to believe your value is what you produce. That your worth is what you earn. That rest is something you survive the week to reach, not something you deserve simply by existing. When the machine removes the need for your labor, that belief does not update. It breaks. The people least prepared for that moment are the ones who worked the hardest. The ones who took the most pride in being indispensable. The ones who made work the whole answer. Losing the job is survivable. Losing the reason to get up is not. That is what Musk is actually asking. Not how do we pay people. How do we build a world where people still feel like they matter when the economy no longer needs them. Nobody in power is seriously working on that answer. The machine didn’t wait.

Dustin

247,028 Aufrufe • vor 3 Monaten

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.

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 Aufrufe • vor 4 Monaten

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.

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 Aufrufe • vor 3 Monaten

Jensen Huang just explained why every company cutting engineers over AI is asking the entirely wrong question. Huang: “People say, I don’t need software engineers because apparently coding is going to be automated.” That was the narrative. Here is what Huang actually did. Huang: “I’ve given AIs to every one of my software engineers and hardware engineers and engineers period. 100% of NVIDIA has AI assistants, AI coders, and they’re busier than ever.” Not fewer engineers. Not smaller teams. Busier than ever. That is the line most companies are getting completely wrong right now. They hear “AI can write code” and immediately start cutting headcount. Huang did the opposite. He armed everyone. Huang: “And so the question is, what is the task versus what is the job? No different than a financial analyst; the task is mess around with spreadsheets, but the job is to make financial advice. The job is to help a customer.” Writing code was always the task. It was never the job. The job is architecture. Knowing what to build. Why it matters. How it fits into a system that actually creates value. Code is the execution layer between the idea and the outcome. Nothing more. When you automate that layer, you don’t eliminate the engineer. You eliminate the bottleneck between what they can envision and what they can ship. The companies using AI to cut headcount are optimizing for cost. The companies using AI to multiply output are optimizing for territory. Nvidia chose territory. Every engineer at the most valuable semiconductor company on Earth now operates with an AI assistant. Not a pilot program. Not an experiment. Company-wide. Every function. Every team. And the result is not less work. It is more work. Faster. At a scale that was physically impossible twelve months ago. The companies that understand the difference between eliminating engineers and unleashing them will build what comes next. The ones that don’t will watch their best talent walk out the door to the ones that did.

Jensen Huang just explained why every company cutting engineers over AI is asking the entirely wrong question. Huang: “People say, I don’t need software engineers because apparently coding is going to be automated.” That was the narrative. Here is what Huang actually did. Huang: “I’ve given AIs to every one of my software engineers and hardware engineers and engineers period. 100% of NVIDIA has AI assistants, AI coders, and they’re busier than ever.” Not fewer engineers. Not smaller teams. Busier than ever. That is the line most companies are getting completely wrong right now. They hear “AI can write code” and immediately start cutting headcount. Huang did the opposite. He armed everyone. Huang: “And so the question is, what is the task versus what is the job? No different than a financial analyst; the task is mess around with spreadsheets, but the job is to make financial advice. The job is to help a customer.” Writing code was always the task. It was never the job. The job is architecture. Knowing what to build. Why it matters. How it fits into a system that actually creates value. Code is the execution layer between the idea and the outcome. Nothing more. When you automate that layer, you don’t eliminate the engineer. You eliminate the bottleneck between what they can envision and what they can ship. The companies using AI to cut headcount are optimizing for cost. The companies using AI to multiply output are optimizing for territory. Nvidia chose territory. Every engineer at the most valuable semiconductor company on Earth now operates with an AI assistant. Not a pilot program. Not an experiment. Company-wide. Every function. Every team. And the result is not less work. It is more work. Faster. At a scale that was physically impossible twelve months ago. The companies that understand the difference between eliminating engineers and unleashing them will build what comes next. The ones that don’t will watch their best talent walk out the door to the ones that did.

Dustin

82,737 Aufrufe • vor 3 Monaten

Elon Musk just said the quiet part out loud about government and AI. Musk: “AI is moving 10 times faster than government, maybe more.” Not slightly ahead. Not a few years out in front. Ten times faster. And pulling away. Every regulatory body on earth runs on the same architecture. Committees form. Hearings are scheduled. Legislation is drafted, debated, revised, and passed. By the time a law exists, the thing it was written to govern has already moved three generations beyond it. That architecture was built for a world that moves at human speed. This world does not. Musk: “The one thing that the government can do is just issue people money.” Not regulate. Not protect. Not steer. Issue money. That is not a policy position. That is a surrender. The most powerful governments on earth, sitting on top of the most sophisticated legal and military infrastructure in human history, reduced to a single remaining function. Sending people checks. Because they cannot move fast enough to do anything else. Now sit with what that actually means. For ten thousand years, the central bargain of civilization was simple. You contribute labor. Society functions. You eat. The system needed you. That bargain is being quietly retired. The machine does not need you to run the factory. Does not need you to process the paperwork. Does not need you to write the code or drive the truck or staff the call center. And the government already knows it. Musk: “Nobody’s gonna starve is what I’m saying.” He is right. The floor is rising. Survival is becoming guaranteed. That should feel like the finish line. For most of human history, it would have been. But here is what nobody is saying out loud. The hard part was never survival. The hard part is what happens to a species that spent ten millennia being defined by its need to survive, the moment that need disappears. Purpose is not something the government can deposit into your account. A check covers rent. It does not answer the question of what you are for. When the thing that organized your days, justified your effort, and gave your life a legible shape gets handed to a machine, you do not automatically inherit freedom. You inherit a void. And a void with a guaranteed income is still a void. The people who will matter in this era are not the ones who cash the check and wait. They are the ones who hear the starting gun in it. For the first time in history, the baseline is solved. Which means the only question left is the one every generation before yours was too buried to ask. What are you actually here to build.

Elon Musk just said the quiet part out loud about government and AI. Musk: “AI is moving 10 times faster than government, maybe more.” Not slightly ahead. Not a few years out in front. Ten times faster. And pulling away. Every regulatory body on earth runs on the same architecture. Committees form. Hearings are scheduled. Legislation is drafted, debated, revised, and passed. By the time a law exists, the thing it was written to govern has already moved three generations beyond it. That architecture was built for a world that moves at human speed. This world does not. Musk: “The one thing that the government can do is just issue people money.” Not regulate. Not protect. Not steer. Issue money. That is not a policy position. That is a surrender. The most powerful governments on earth, sitting on top of the most sophisticated legal and military infrastructure in human history, reduced to a single remaining function. Sending people checks. Because they cannot move fast enough to do anything else. Now sit with what that actually means. For ten thousand years, the central bargain of civilization was simple. You contribute labor. Society functions. You eat. The system needed you. That bargain is being quietly retired. The machine does not need you to run the factory. Does not need you to process the paperwork. Does not need you to write the code or drive the truck or staff the call center. And the government already knows it. Musk: “Nobody’s gonna starve is what I’m saying.” He is right. The floor is rising. Survival is becoming guaranteed. That should feel like the finish line. For most of human history, it would have been. But here is what nobody is saying out loud. The hard part was never survival. The hard part is what happens to a species that spent ten millennia being defined by its need to survive, the moment that need disappears. Purpose is not something the government can deposit into your account. A check covers rent. It does not answer the question of what you are for. When the thing that organized your days, justified your effort, and gave your life a legible shape gets handed to a machine, you do not automatically inherit freedom. You inherit a void. And a void with a guaranteed income is still a void. The people who will matter in this era are not the ones who cash the check and wait. They are the ones who hear the starting gun in it. For the first time in history, the baseline is solved. Which means the only question left is the one every generation before yours was too buried to ask. What are you actually here to build.

Dustin

63,232 Aufrufe • vor 3 Monaten

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

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

slash1s

60,755 Aufrufe • vor 17 Tagen

Marc Andreessen just collapsed a fifty-year assumption in one sentence. Andreessen: “I’m not sure there will even be a salient concept of a programming language in the way that we understand it today.” Not declining. Not evolving. Gone. For fifty years, humans learned machine syntax to command computers. We bent our cognition to fit their grammar. We built entire careers on how fluently we could speak a language machines wrote the rules for. That was always backwards. The correction is arriving faster than the industry will say out loud. Andreessen didn’t stop there. Andreessen: “You may not need user interfaces.” Then came the only question left. Who uses software in the future? Other bots. Follow that to its end. The screen. The dashboard. The browser. The app. The dropdown menu. Every interface ever built assumed a human on the other end who needed the world made legible. If the user is a machine, none of that is necessary. The entire visual layer of computing was built for biological eyes. When the primary users are no longer biological, that layer doesn’t get updated. It gets stripped. Andreessen drew the comparison himself. Not long ago, 99% of humanity was behind a plow. The world spent generations asking what people would do when farming disappeared. The answer was everything worth doing. We are at that exact moment again. Except this time, the plow is a keyboard. Andreessen: “I’m going to tell the thing what I need, and it’s going to do it in whatever way is most optimal.” That sentence deletes the entire skills economy built around execution. Not judgment. Not taste. Not the ability to want the right things. Just execution. That part is over. Which means the only thing left that matters is the quality of what you want. Most people have spent their entire careers getting better at building. Almost no one has spent that time getting better at knowing what to build. That gap is about to become the only gap that matters. The friction of execution is gone. What you can imagine is what you can build. The question is whether you’ve ever trained that muscle. Most people haven’t.

Marc Andreessen just collapsed a fifty-year assumption in one sentence. Andreessen: “I’m not sure there will even be a salient concept of a programming language in the way that we understand it today.” Not declining. Not evolving. Gone. For fifty years, humans learned machine syntax to command computers. We bent our cognition to fit their grammar. We built entire careers on how fluently we could speak a language machines wrote the rules for. That was always backwards. The correction is arriving faster than the industry will say out loud. Andreessen didn’t stop there. Andreessen: “You may not need user interfaces.” Then came the only question left. Who uses software in the future? Other bots. Follow that to its end. The screen. The dashboard. The browser. The app. The dropdown menu. Every interface ever built assumed a human on the other end who needed the world made legible. If the user is a machine, none of that is necessary. The entire visual layer of computing was built for biological eyes. When the primary users are no longer biological, that layer doesn’t get updated. It gets stripped. Andreessen drew the comparison himself. Not long ago, 99% of humanity was behind a plow. The world spent generations asking what people would do when farming disappeared. The answer was everything worth doing. We are at that exact moment again. Except this time, the plow is a keyboard. Andreessen: “I’m going to tell the thing what I need, and it’s going to do it in whatever way is most optimal.” That sentence deletes the entire skills economy built around execution. Not judgment. Not taste. Not the ability to want the right things. Just execution. That part is over. Which means the only thing left that matters is the quality of what you want. Most people have spent their entire careers getting better at building. Almost no one has spent that time getting better at knowing what to build. That gap is about to become the only gap that matters. The friction of execution is gone. What you can imagine is what you can build. The question is whether you’ve ever trained that muscle. Most people haven’t.

Dustin

66,373 Aufrufe • vor 3 Monaten

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

680,508 Aufrufe • vor 10 Tagen

Elon Musk just told you the job is dying. Most people heard a prediction. A few heard a prison door opening. Musk: “In less than 20 years, working at all will be optional.” That is not a policy suggestion. That is a countdown. For three hundred years, the human blueprint has been identical. You are born. You move to the city. You rent a box near the office. You trade your body and your hours for the right to exist. You do this until you are old. Then you stop. Then you die. The entire model runs on one assumption. That human labor is the only engine. AI and robotics delete that assumption. When the machine handles production at a scale no human crew can match, the forced migration to the city evaporates. The commute evaporates. The cubicle evaporates. The alarm clock that owns your nervous system for forty years evaporates. Musk: “I think it won’t be the case that you have to be in a city for a job.” The city was never a choice. It was a requirement disguised as ambition. You moved to the noise and the concrete and the $4,000 rent because the paycheck lived there. Remove the paycheck from the equation and the geography changes overnight. You can live in the mountains. On the coast. In the silence of a town most people have never heard of. You can wake up to nothing but trees and cold air and the complete absence of anyone else’s schedule. That is not a fantasy. That is the math resolving. But here is where most people break. They hear “work is optional” and they see emptiness. A species with nothing to do. Billions of people staring at screens until their minds dissolve. That fear tells you everything about what the system has already done to us. We confused labor with purpose. The grind with meaning. The paycheck with proof that we matter. Musk: “In the same way that you could grow your own vegetables in your garden.” The analogy is precise. You do not grow tomatoes because the economy demands it. You grow them because something in you wants to build a thing with your hands and watch it come alive. That instinct does not disappear when the job does. It gets unleashed. The artist who spent twenty years doing accounting finally paints. The engineer who always wanted to build something of her own finally builds it. The kid in a small town who could never afford to take the risk finally takes it. Work does not vanish. Forced work vanishes. What replaces it is creation without a gun to your head. This is the part that keeps me up at night. We are standing at the edge of the largest liberation in human history. And the loudest voices in the room are begging to stay in the cell. They want the commute. They want the boss. They want the structure that tells them when to eat and when to sleep and when they are allowed to think about their own life. Because freedom without a template is terrifying. The next twenty years will not test our technology. The technology is already ahead of schedule. They will test whether the species can handle what it has been asking for since the beginning of civilization. Time. Space. Silence. And the unbearable weight of choosing what your life actually means when no one is forcing the answer. That is not a prediction. That is the final exam. And nobody is ready.

Elon Musk just told you the job is dying. Most people heard a prediction. A few heard a prison door opening. Musk: “In less than 20 years, working at all will be optional.” That is not a policy suggestion. That is a countdown. For three hundred years, the human blueprint has been identical. You are born. You move to the city. You rent a box near the office. You trade your body and your hours for the right to exist. You do this until you are old. Then you stop. Then you die. The entire model runs on one assumption. That human labor is the only engine. AI and robotics delete that assumption. When the machine handles production at a scale no human crew can match, the forced migration to the city evaporates. The commute evaporates. The cubicle evaporates. The alarm clock that owns your nervous system for forty years evaporates. Musk: “I think it won’t be the case that you have to be in a city for a job.” The city was never a choice. It was a requirement disguised as ambition. You moved to the noise and the concrete and the $4,000 rent because the paycheck lived there. Remove the paycheck from the equation and the geography changes overnight. You can live in the mountains. On the coast. In the silence of a town most people have never heard of. You can wake up to nothing but trees and cold air and the complete absence of anyone else’s schedule. That is not a fantasy. That is the math resolving. But here is where most people break. They hear “work is optional” and they see emptiness. A species with nothing to do. Billions of people staring at screens until their minds dissolve. That fear tells you everything about what the system has already done to us. We confused labor with purpose. The grind with meaning. The paycheck with proof that we matter. Musk: “In the same way that you could grow your own vegetables in your garden.” The analogy is precise. You do not grow tomatoes because the economy demands it. You grow them because something in you wants to build a thing with your hands and watch it come alive. That instinct does not disappear when the job does. It gets unleashed. The artist who spent twenty years doing accounting finally paints. The engineer who always wanted to build something of her own finally builds it. The kid in a small town who could never afford to take the risk finally takes it. Work does not vanish. Forced work vanishes. What replaces it is creation without a gun to your head. This is the part that keeps me up at night. We are standing at the edge of the largest liberation in human history. And the loudest voices in the room are begging to stay in the cell. They want the commute. They want the boss. They want the structure that tells them when to eat and when to sleep and when they are allowed to think about their own life. Because freedom without a template is terrifying. The next twenty years will not test our technology. The technology is already ahead of schedule. They will test whether the species can handle what it has been asking for since the beginning of civilization. Time. Space. Silence. And the unbearable weight of choosing what your life actually means when no one is forcing the answer. That is not a prediction. That is the final exam. And nobody is ready.

Dustin

111,613 Aufrufe • vor 3 Monaten

Larry Ellison says today's AI models are no longer just inferencing; they reason like we do These systems handle deduction, calculation, and strategy far faster than people "at Oracle, most code is now AI-generated" We declare our intent; the model writes the procedure

Larry Ellison says today's AI models are no longer just inferencing; they reason like we do These systems handle deduction, calculation, and strategy far faster than people "at Oracle, most code is now AI-generated" We declare our intent; the model writes the procedure

Haider.

172,553 Aufrufe • vor 8 Monaten

Andrej Karpathy just told you exactly what humans will be used for in the AI era. Not partners. Not masters. He used the word “actuators.” Karpathy: “The intelligence ends up puppeteering almost a little bit, like humanity. Humans are kind of like its actuators. But humans are also like its sensors.” This is not a novelist guessing at the future. This is a founding researcher at OpenAI and former Director of AI at Tesla. One of the most respected minds in the field, and one of the few willing to say out loud what the rest are thinking. He is not describing a risk. He is describing a design. In any system, the processor decides. Sensors collect. Actuators execute. The system does not consult its actuators. We are no longer the processor. Karpathy: “Society will kind of reshape in a certain way to serve that. Humans will be serving those needs of that machine.” The machine does not adapt to us. We adapt to it. We become the biological layer it runs on. We perceive what it cannot perceive. We move what it cannot move. We are the nervous system of something that no longer requires our judgment. Most people are still waiting for AI to become a tool they can direct. He helped build it. He just told you that you are the tool.

Andrej Karpathy just told you exactly what humans will be used for in the AI era. Not partners. Not masters. He used the word “actuators.” Karpathy: “The intelligence ends up puppeteering almost a little bit, like humanity. Humans are kind of like its actuators. But humans are also like its sensors.” This is not a novelist guessing at the future. This is a founding researcher at OpenAI and former Director of AI at Tesla. One of the most respected minds in the field, and one of the few willing to say out loud what the rest are thinking. He is not describing a risk. He is describing a design. In any system, the processor decides. Sensors collect. Actuators execute. The system does not consult its actuators. We are no longer the processor. Karpathy: “Society will kind of reshape in a certain way to serve that. Humans will be serving those needs of that machine.” The machine does not adapt to us. We adapt to it. We become the biological layer it runs on. We perceive what it cannot perceive. We move what it cannot move. We are the nervous system of something that no longer requires our judgment. Most people are still waiting for AI to become a tool they can direct. He helped build it. He just told you that you are the tool.

Dustin

59,474 Aufrufe • vor 3 Monaten

Sam Altman just told you exactly how OpenAI treats the human race. Not in a leaked memo. Not through a whistleblower. On camera. In his own words. Altman: “I think one of the most important strategic insights in the history of OpenAI was deciding we were gonna pursue iterative deployment.” The most important move in the history of the company was to release the technology before they understood it. Not after it was safe. Before. Altman: “Society and technology are a co-evolving system.” Co-evolution means neither side is driving. The machine changes us. We change the machine. Nobody is steering the outcome. This is not a product launch philosophy. This is an admission that the experiment was always designed to be run on us. Altman: “I don’t think we’re gonna solve that, like, thinking really hard about it theoretically. We’re gonna have to, like, learn from the contact with reality.” Contact with reality. That is the phrase the CEO of the most powerful AI company on Earth chose to describe what happens when his technology meets eight billion people. Not careful integration. Not measured rollout. Contact with reality. The language of test pilots describing what happens when an untested airframe hits the atmosphere. The entire promise of AI safety was that the machine would be understood before it was unleashed. Altman just admitted that promise was always a fantasy. You cannot model how intelligence reshapes civilization by running simulations. The second and third order effects are invisible until they detonate. So they shipped it. Altman: “You have to learn as you go. You have to adapt with a tight feedback loop.” Tight feedback loop means they watch what breaks. They measure the collision between human psychology and machine output in real time. Every conversation you have with ChatGPT is a data point in a civilizational stress test you never consented to. Every prompt. Every confession. Every question you would never ask another human being. That is the feedback loop. You are not the customer. You are the contact with reality. Philosophers spent centuries asking whether humanity would ever encounter an intelligence that learned from us faster than we could process what it was doing. That is not a theoretical question anymore. It is running on your phone right now. And the man building it just told you the only way to understand what it does to us is to let it happen. No simulation. No safety net. No control group. Just the experiment, running at the speed of conversation, on a species that will not be the same one that started it.

Sam Altman just told you exactly how OpenAI treats the human race. Not in a leaked memo. Not through a whistleblower. On camera. In his own words. Altman: “I think one of the most important strategic insights in the history of OpenAI was deciding we were gonna pursue iterative deployment.” The most important move in the history of the company was to release the technology before they understood it. Not after it was safe. Before. Altman: “Society and technology are a co-evolving system.” Co-evolution means neither side is driving. The machine changes us. We change the machine. Nobody is steering the outcome. This is not a product launch philosophy. This is an admission that the experiment was always designed to be run on us. Altman: “I don’t think we’re gonna solve that, like, thinking really hard about it theoretically. We’re gonna have to, like, learn from the contact with reality.” Contact with reality. That is the phrase the CEO of the most powerful AI company on Earth chose to describe what happens when his technology meets eight billion people. Not careful integration. Not measured rollout. Contact with reality. The language of test pilots describing what happens when an untested airframe hits the atmosphere. The entire promise of AI safety was that the machine would be understood before it was unleashed. Altman just admitted that promise was always a fantasy. You cannot model how intelligence reshapes civilization by running simulations. The second and third order effects are invisible until they detonate. So they shipped it. Altman: “You have to learn as you go. You have to adapt with a tight feedback loop.” Tight feedback loop means they watch what breaks. They measure the collision between human psychology and machine output in real time. Every conversation you have with ChatGPT is a data point in a civilizational stress test you never consented to. Every prompt. Every confession. Every question you would never ask another human being. That is the feedback loop. You are not the customer. You are the contact with reality. Philosophers spent centuries asking whether humanity would ever encounter an intelligence that learned from us faster than we could process what it was doing. That is not a theoretical question anymore. It is running on your phone right now. And the man building it just told you the only way to understand what it does to us is to let it happen. No simulation. No safety net. No control group. Just the experiment, running at the speed of conversation, on a species that will not be the same one that started it.

Dustin

27,714 Aufrufe • vor 2 Monaten

Jensen Huang just made the case that the smartest person in the room is now the most replaceable person on earth. Huang: “The definition of smart is somebody who’s intelligent, solve problems, technical. But I find that that’s a commodity. And we’re about to prove that artificial intelligence is able to handle that part easiest.” The skill you built your entire identity around was the first thing the machine replicated. Not the hardest part. The easiest. Huang: “People who are able to see around corners are truly, truly smart. And their value is incredible. To be able to preempt problems before they show up, just because you feel the vibe.” Huang: “That vibe came from a combination of data, analysis, first principle, life experience, wisdom, sensing other people.” The vibe is not intuition. It is decades of failed bets, human friction, and first-principles thinking compressed into a single read no model can replicate. You cannot prompt your way to it. You earn it by surviving things that had no instructions. Huang: “I think long term the definition of smart is someone who sits at that intersection of being technically astute, but human empathy and having the ability to infer the unspoken, around the corners, the unknowables.” Every institution you ever passed through graded you on the one thing the machine now does for free. The thing they never tested you on is the only thing that still matters. Huang: “And that person might actually score horribly on the SAT.” The SAT did not measure intelligence. It measured obedience to structure. The future does not reward what you can solve inside a framework someone handed you. It rewards what you can see when no framework exists. The machine did not replace human intelligence. It revealed that what we spent a century calling intelligence was never intelligence at all. The people who memorized the answers are about to work for the people who sensed the questions before anyone thought to ask.

Jensen Huang just made the case that the smartest person in the room is now the most replaceable person on earth. Huang: “The definition of smart is somebody who’s intelligent, solve problems, technical. But I find that that’s a commodity. And we’re about to prove that artificial intelligence is able to handle that part easiest.” The skill you built your entire identity around was the first thing the machine replicated. Not the hardest part. The easiest. Huang: “People who are able to see around corners are truly, truly smart. And their value is incredible. To be able to preempt problems before they show up, just because you feel the vibe.” Huang: “That vibe came from a combination of data, analysis, first principle, life experience, wisdom, sensing other people.” The vibe is not intuition. It is decades of failed bets, human friction, and first-principles thinking compressed into a single read no model can replicate. You cannot prompt your way to it. You earn it by surviving things that had no instructions. Huang: “I think long term the definition of smart is someone who sits at that intersection of being technically astute, but human empathy and having the ability to infer the unspoken, around the corners, the unknowables.” Every institution you ever passed through graded you on the one thing the machine now does for free. The thing they never tested you on is the only thing that still matters. Huang: “And that person might actually score horribly on the SAT.” The SAT did not measure intelligence. It measured obedience to structure. The future does not reward what you can solve inside a framework someone handed you. It rewards what you can see when no framework exists. The machine did not replace human intelligence. It revealed that what we spent a century calling intelligence was never intelligence at all. The people who memorized the answers are about to work for the people who sensed the questions before anyone thought to ask.

Dustin

107,532 Aufrufe • vor 1 Tag

"Constipated." That is the word now being used for the private credit market. And it is exactly what this looks like. The private credit story is changing. For months it was framed as a liquidity problem. Investors trying to pull their money out. That is still a huge problem. BlackRock just had a couple of funds suffering big runs. But there is a bigger one. It is no longer just the investors who want out. It is the investors outside who no longer want in. And that is the much bigger story. Because the private credit boom was built on flows. Constant inflows from wealth managers, pensions, insurance companies, and the general public. That is how big it got. The machine has to keep moving. Money comes in. Loans get made. Funds grow. Redemptions get handled. Managers collect their fees. Everyone pretends it is calm because the marks are smooth and the exits are limited. Now the machine is reversing. Reuters reported US direct lending issuance in the three months ending May was down roughly 40% from the first quarter. Issuance to private-equity-backed borrowers dropped nearly 37%. Volume tied to leveraged buyouts fell about 34%. So this is no longer just a redemption story. The exits are clogged. New money is hesitant. Sellers will not cut prices, and buyers will not pay yesterday's valuations. Credit funds are handling redemptions. Leveraged loans are showing strain. And publicly traded BDCs are not rebounding, even as the broader market soars. So the question is no longer whether investors are still withdrawing. They are, and it is accelerating. It is not about the people inside who want out. It is about the people outside who no longer want in. That is the bigger problem. It pushes us deeper into stage two, and the odds of stage three go up from here.

"Constipated." That is the word now being used for the private credit market. And it is exactly what this looks like. The private credit story is changing. For months it was framed as a liquidity problem. Investors trying to pull their money out. That is still a huge problem. BlackRock just had a couple of funds suffering big runs. But there is a bigger one. It is no longer just the investors who want out. It is the investors outside who no longer want in. And that is the much bigger story. Because the private credit boom was built on flows. Constant inflows from wealth managers, pensions, insurance companies, and the general public. That is how big it got. The machine has to keep moving. Money comes in. Loans get made. Funds grow. Redemptions get handled. Managers collect their fees. Everyone pretends it is calm because the marks are smooth and the exits are limited. Now the machine is reversing. Reuters reported US direct lending issuance in the three months ending May was down roughly 40% from the first quarter. Issuance to private-equity-backed borrowers dropped nearly 37%. Volume tied to leveraged buyouts fell about 34%. So this is no longer just a redemption story. The exits are clogged. New money is hesitant. Sellers will not cut prices, and buyers will not pay yesterday's valuations. Credit funds are handling redemptions. Leveraged loans are showing strain. And publicly traded BDCs are not rebounding, even as the broader market soars. So the question is no longer whether investors are still withdrawing. They are, and it is accelerating. It is not about the people inside who want out. It is about the people outside who no longer want in. That is the bigger problem. It pushes us deeper into stage two, and the odds of stage three go up from here.

Jeffrey P. Snider

24,551 Aufrufe • vor 22 Tagen

Dario Amodei, CEO of Anthropic, just shortened your career timeline. His own engineers have stopped writing code. 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 advanced AI on Earth are already being replaced by what they built. Not in theory. Not in a forecast. Inside the building. Right now. Amodei: “I think we might be 6 to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” Six to twelve months. Not from automating busywork. From replacing the full scope of what a software engineer does. Architecture. Logic. Debugging. Deployment. The entire chain. Software engineering is not some fading trade. It is the highest-paid, highest-demand, most protected skill the modern economy ever produced. And the man running a frontier lab just gave it a six-month shelf life. If the most technically sophisticated job in the economy falls first, nothing beneath it is safe. That is the inversion no one saw coming. The assumption was always that AI would eat from the bottom. Routine work. Data entry. Simple automation. It started at the top. Engineers first. Then analysts. Then strategists. Then the managers overseeing work that no longer needs them. The displacement doesn’t crawl upward. It cascades downward. Starting with the people closest to the technology itself. Amodei: “If I had to guess, I would guess that this goes faster than people imagine, and that that key element of code, and increasingly research, going faster than we imagine.” Not just code. Research. Hypotheses. Experiments. Interpretation. Discovery itself. If AI closes that loop, it doesn’t just write software. It improves itself. Every iteration compresses the timeline further. Amodei: “It’s very hard for me to see how it could take longer than a few years.” He is not selling optimism. He is setting a ceiling. A few years. Maximum. For AI to absorb the two most important intellectual functions in the economy. The window to position yourself is not a decade. It is already closing.

Dario Amodei, CEO of Anthropic, just shortened your career timeline. His own engineers have stopped writing code. 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 advanced AI on Earth are already being replaced by what they built. Not in theory. Not in a forecast. Inside the building. Right now. Amodei: “I think we might be 6 to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” Six to twelve months. Not from automating busywork. From replacing the full scope of what a software engineer does. Architecture. Logic. Debugging. Deployment. The entire chain. Software engineering is not some fading trade. It is the highest-paid, highest-demand, most protected skill the modern economy ever produced. And the man running a frontier lab just gave it a six-month shelf life. If the most technically sophisticated job in the economy falls first, nothing beneath it is safe. That is the inversion no one saw coming. The assumption was always that AI would eat from the bottom. Routine work. Data entry. Simple automation. It started at the top. Engineers first. Then analysts. Then strategists. Then the managers overseeing work that no longer needs them. The displacement doesn’t crawl upward. It cascades downward. Starting with the people closest to the technology itself. Amodei: “If I had to guess, I would guess that this goes faster than people imagine, and that that key element of code, and increasingly research, going faster than we imagine.” Not just code. Research. Hypotheses. Experiments. Interpretation. Discovery itself. If AI closes that loop, it doesn’t just write software. It improves itself. Every iteration compresses the timeline further. Amodei: “It’s very hard for me to see how it could take longer than a few years.” He is not selling optimism. He is setting a ceiling. A few years. Maximum. For AI to absorb the two most important intellectual functions in the economy. The window to position yourself is not a decade. It is already closing.

Dustin

16,132 Aufrufe • vor 3 Monaten

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

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

slash1s

290,782 Aufrufe • vor 9 Tagen

Larry Ellison just put a price on police accountability. It is $70. Everyone is arguing about AI copyright law. Ellison is building a total surveillance architecture for American law enforcement. He started by gutting the hardware racket. Larry Ellison: “Our body cameras cost 70 bucks. Normal body camera costs $7,000. Our body cameras are simply lenses, two lenses attached to your vest, attached to the smartphone you’re wearing.” A body camera used to be $7,000 of proprietary hardware. Ellison reduced it to a $70 lens leeching compute off the phone in the officer’s pocket. That is not a product improvement. That is the deliberate destruction of a pricing structure built to limit how many eyes the state can afford to open. Slash the cost of observation by 99% and you do not upgrade the system. You make total deployment a mathematical certainty. But the cheap glass is bait. The real architecture begins after the lens. Ellison: “The camera is always on. You don’t turn it on and off. The truth is, we don’t really turn it off.” For decades the fatal flaw in police accountability was a button. One human decided when the recording started. The same human decided when it stopped. Footage vanished at the exact moment it mattered most. Ellison deleted the button. Ellison: “What we do is, we record it so no one can see it. But no one can get into that recording without a court order.” The officer still feels private. They are not. The hardware writes continuously to a sealed record only a judge can unlock. Unrecorded space around an armed agent of the state just became a legal fiction. But recording everything creates an impossible problem. A million hours of footage is worthless if nobody watches it. You cannot hire enough humans to review every shift, every stop, every escalation. So the data rots on a server. Always arriving after the damage is done. Ellison solved it the only way that scales. He replaced the watchers. Ellison: “It’s not people that are looking at those cameras, it’s AI that’s looking at the cameras.” An autonomous system watches every frame in real time. Every escalation flagged. Every use of force scored. Ellison: “Every police officer is going to be supervised at all times. And if there’s a problem, AI will report the problem.” The chain of command for armed state authority just became a machine that does not sleep, does not cover for its own, and does not forget. We spent a decade asking who watches the watchers. Ellison did not reform the watchers. He made them obsolete. AI is not just coming for white-collar jobs. It is becoming the permanent, unblinking authority over the only people in your city authorized to kill. $70 and an algorithm that never looks away. That is the new chain of command.

Larry Ellison just put a price on police accountability. It is $70. Everyone is arguing about AI copyright law. Ellison is building a total surveillance architecture for American law enforcement. He started by gutting the hardware racket. Larry Ellison: “Our body cameras cost 70 bucks. Normal body camera costs $7,000. Our body cameras are simply lenses, two lenses attached to your vest, attached to the smartphone you’re wearing.” A body camera used to be $7,000 of proprietary hardware. Ellison reduced it to a $70 lens leeching compute off the phone in the officer’s pocket. That is not a product improvement. That is the deliberate destruction of a pricing structure built to limit how many eyes the state can afford to open. Slash the cost of observation by 99% and you do not upgrade the system. You make total deployment a mathematical certainty. But the cheap glass is bait. The real architecture begins after the lens. Ellison: “The camera is always on. You don’t turn it on and off. The truth is, we don’t really turn it off.” For decades the fatal flaw in police accountability was a button. One human decided when the recording started. The same human decided when it stopped. Footage vanished at the exact moment it mattered most. Ellison deleted the button. Ellison: “What we do is, we record it so no one can see it. But no one can get into that recording without a court order.” The officer still feels private. They are not. The hardware writes continuously to a sealed record only a judge can unlock. Unrecorded space around an armed agent of the state just became a legal fiction. But recording everything creates an impossible problem. A million hours of footage is worthless if nobody watches it. You cannot hire enough humans to review every shift, every stop, every escalation. So the data rots on a server. Always arriving after the damage is done. Ellison solved it the only way that scales. He replaced the watchers. Ellison: “It’s not people that are looking at those cameras, it’s AI that’s looking at the cameras.” An autonomous system watches every frame in real time. Every escalation flagged. Every use of force scored. Ellison: “Every police officer is going to be supervised at all times. And if there’s a problem, AI will report the problem.” The chain of command for armed state authority just became a machine that does not sleep, does not cover for its own, and does not forget. We spent a decade asking who watches the watchers. Ellison did not reform the watchers. He made them obsolete. AI is not just coming for white-collar jobs. It is becoming the permanent, unblinking authority over the only people in your city authorized to kill. $70 and an algorithm that never looks away. That is the new chain of command.

Dustin

20,871 Aufrufe • vor 2 Monaten

A robot just replaced the human who draws your blood, and it is already inside European hospitals right now. The device called Aletta is CE-marked, the European equivalent of FDA approval and it is already operating on real patients. Vitestro built a machine that maps your veins using AI powered Doppler ultrasound, locks onto the right one with submillimeter precision, inserts the needle, fills the tubes, removes the needle and applies the bandage completely on its own. No human hands touch you during the procedure and one trained supervisor can oversee up to three of these machines running simultaneously. And 98% of patients who went through it said they would accept the procedure again. The machine does not care if your veins are difficult or your skin tone, body type, or whether past draws were painful. It finds a vein on almost every patient regardless and roughly 1.4 billion blood draws happen in the United States alone every single year. Every one of those is currently done by a human being and that human has a job title, phlebotomist. There are roughly 130,000 of them working in the US today and that job is now directly in the crosshairs of this technology. Northwestern Medicine, one of the most prestigious hospital systems in America already signed a multi-year collaboration agreement with Vitestro to bring this machine to US hospitals.

A robot just replaced the human who draws your blood, and it is already inside European hospitals right now. The device called Aletta is CE-marked, the European equivalent of FDA approval and it is already operating on real patients. Vitestro built a machine that maps your veins using AI powered Doppler ultrasound, locks onto the right one with submillimeter precision, inserts the needle, fills the tubes, removes the needle and applies the bandage completely on its own. No human hands touch you during the procedure and one trained supervisor can oversee up to three of these machines running simultaneously. And 98% of patients who went through it said they would accept the procedure again. The machine does not care if your veins are difficult or your skin tone, body type, or whether past draws were painful. It finds a vein on almost every patient regardless and roughly 1.4 billion blood draws happen in the United States alone every single year. Every one of those is currently done by a human being and that human has a job title, phlebotomist. There are roughly 130,000 of them working in the US today and that job is now directly in the crosshairs of this technology. Northwestern Medicine, one of the most prestigious hospital systems in America already signed a multi-year collaboration agreement with Vitestro to bring this machine to US hospitals.

StockMarket.News

546,564 Aufrufe • vor 3 Monaten