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Jensen Huang just described the most fundamental shift in computing since the invention of the computer itself. Almost no one has processed it. Huang: “We went from a retrieval-based computing system to a generative-based computing system.” For fifty years, a computer was a filing cabinet. You made something. Saved...

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Dustin

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25,402 Aufrufe • vor 3 Monaten •via X (Twitter)

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For 60 years every computer ever built did the same thing. Stored information and retrieved it on demand. Jensen Huang just explained why that era is over and what replaces it. His framing was the clearest I have ever heard. Think about everything a computer has ever done for you. You wrote a document, you saved it to a file. You took a photo, it saved to a file. You recorded music, it saved to a file. When you wanted it back, you retrieved it from a disc. That is it. That is 60 years of computing. Store and retrieve. He pointed out something hiding in plain sight. We call them data centers. Not computer centers. Because we were not really computing anything meaningful. We were storing data that you retrieved based on what you tapped on your phone. Then he explained what changed. Every time you give AI a prompt today, the response is produced originally in real time. It is not retrieved from storage. It is generated fresh based on your specific context, your specific question, your specific moment. What you see is completely different from what anyone else sees because it was made for you. Jensen said every pixel you see, every word you read, every video you watch in the future will be originally generated. Not retrieved. 60 years of computing was about building better storage and faster retrieval. The entire paradigm flipped overnight. He said this simply: we went from a retrieval industry to a generation industry. And the machines that generate intelligence are what Nvidia builds. The buildings used to be called data centers because they stored data. Nobody has renamed them yet. But the job description changed completely.
1:38

For 60 years every computer ever built did the same thing. Stored information and retrieved it on demand. Jensen Huang just explained why that era is over and what replaces it. His framing was the clearest I have ever heard. Think about everything a computer has ever done for you. You wrote a document, you saved it to a file. You took a photo, it saved to a file. You recorded music, it saved to a file. When you wanted it back, you retrieved it from a disc. That is it. That is 60 years of computing. Store and retrieve. He pointed out something hiding in plain sight. We call them data centers. Not computer centers. Because we were not really computing anything meaningful. We were storing data that you retrieved based on what you tapped on your phone. Then he explained what changed. Every time you give AI a prompt today, the response is produced originally in real time. It is not retrieved from storage. It is generated fresh based on your specific context, your specific question, your specific moment. What you see is completely different from what anyone else sees because it was made for you. Jensen said every pixel you see, every word you read, every video you watch in the future will be originally generated. Not retrieved. 60 years of computing was about building better storage and faster retrieval. The entire paradigm flipped overnight. He said this simply: we went from a retrieval industry to a generation industry. And the machines that generate intelligence are what Nvidia builds. The buildings used to be called data centers because they stored data. Nobody has renamed them yet. But the job description changed completely.

Ihtesham Ali

30,059 Aufrufe • vor 26 Tagen

Jensen Huang at GTC: "I expect data center build out to reach a trillion dollars, and I am fairly certain we're going to reach that very soon." "General purpose computing has run its course, and that we need a new computing approach." "In the past we wrote the software and we ran it on computers. In the future, the computer is going to generate the tokens for the software." "The computer has become a generator of tokens, not a retrieval of files."
1:47

Jensen Huang at GTC: "I expect data center build out to reach a trillion dollars, and I am fairly certain we're going to reach that very soon." "General purpose computing has run its course, and that we need a new computing approach." "In the past we wrote the software and we ran it on computers. In the future, the computer is going to generate the tokens for the software." "The computer has become a generator of tokens, not a retrieval of files."

vitrupo

55,971 Aufrufe • vor 1 Jahr

Jensen Huang just reframed the entire history of computing in two minutes. The argument is deceptively simple, but once you see it you can't unsee it. Every single piece of software ever built, every app, every website, every search engine, every platform operated on exactly the same fundamental principle. Someone creates content, it gets stored somewhere and when you ask for it, the system retrieves it. Google indexes the web and retrieves the right page, YouTube encodes your video and retrieves it when someone clicks, Amazon photographs every product in its catalog and retrieves the listing that matches your search. Every recommender system, every ad platform, every social feed, all of it, without exception, is a retrieval operation dressed up in a user interface and we called it the Information Age. But strip away the branding and what you had, for 30 consecutive years, was an extraordinarily sophisticated filing cabinet. The smartest engineers in the world spent their careers optimizing how fast you could put things in and pull things out. Generative AI doesn't just improve that system but rather replaces the entire premise of it. Instead of retrieving content that was pre-recorded by someone else, AI generates it from scratch, in real time, calibrated to your exact context, your specific intent, the precise ground truth of that moment. The same question asked twice gets two different answers, both tailored to what the system knows about you right now. There is no file being pulled or a pre-recorded version, the content is being synthesized on the fly from a compressed model of human knowledge, shaped to fit exactly what you need. The implications of this for the companies that built the retrieval era are profound and already starting to show. Google's click-through rates on organic search results have dropped 61% since AI Overviews rolled out, because users are getting answers directly instead of clicking through to files. Gartner projects traditional search engine query volume drops 25% by the end of 2026 as users migrate to generative interfaces. And yet this is exactly what Jensen predicted, in the old world, the computing bottleneck was storage and retrieval, you needed hard drives, bandwidth, and CDNs. In the new world, the bottleneck is computation, you need the raw processing power to generate tokens at scale, millions of times per second, for millions of simultaneous users. Inference computing demand has grown roughly ten thousand times in the last two years alone. That shift is precisely why Nvidia's revenue opportunity forecast just jumped from $500 billion through 2026 to $1 trillion through 2027. The retrieval era needed CPUs and storage and the generative era needs GPUs, token factories, and inference infrastructure at a scale never built before and Nvidia builds the engine underneath all of it. Jensen has been making this argument since 2024. Most people wrote it off as a chip salesman talking his book but two years later, it's the architecture of the entire industry.
1:54

Jensen Huang just reframed the entire history of computing in two minutes. The argument is deceptively simple, but once you see it you can't unsee it. Every single piece of software ever built, every app, every website, every search engine, every platform operated on exactly the same fundamental principle. Someone creates content, it gets stored somewhere and when you ask for it, the system retrieves it. Google indexes the web and retrieves the right page, YouTube encodes your video and retrieves it when someone clicks, Amazon photographs every product in its catalog and retrieves the listing that matches your search. Every recommender system, every ad platform, every social feed, all of it, without exception, is a retrieval operation dressed up in a user interface and we called it the Information Age. But strip away the branding and what you had, for 30 consecutive years, was an extraordinarily sophisticated filing cabinet. The smartest engineers in the world spent their careers optimizing how fast you could put things in and pull things out. Generative AI doesn't just improve that system but rather replaces the entire premise of it. Instead of retrieving content that was pre-recorded by someone else, AI generates it from scratch, in real time, calibrated to your exact context, your specific intent, the precise ground truth of that moment. The same question asked twice gets two different answers, both tailored to what the system knows about you right now. There is no file being pulled or a pre-recorded version, the content is being synthesized on the fly from a compressed model of human knowledge, shaped to fit exactly what you need. The implications of this for the companies that built the retrieval era are profound and already starting to show. Google's click-through rates on organic search results have dropped 61% since AI Overviews rolled out, because users are getting answers directly instead of clicking through to files. Gartner projects traditional search engine query volume drops 25% by the end of 2026 as users migrate to generative interfaces. And yet this is exactly what Jensen predicted, in the old world, the computing bottleneck was storage and retrieval, you needed hard drives, bandwidth, and CDNs. In the new world, the bottleneck is computation, you need the raw processing power to generate tokens at scale, millions of times per second, for millions of simultaneous users. Inference computing demand has grown roughly ten thousand times in the last two years alone. That shift is precisely why Nvidia's revenue opportunity forecast just jumped from $500 billion through 2026 to $1 trillion through 2027. The retrieval era needed CPUs and storage and the generative era needs GPUs, token factories, and inference infrastructure at a scale never built before and Nvidia builds the engine underneath all of it. Jensen has been making this argument since 2024. Most people wrote it off as a chip salesman talking his book but two years later, it's the architecture of the entire industry.

Milk Road AI

17,890 Aufrufe • vor 2 Monaten

Jensen Huang just replaced the most important metric in global economics. Not trade volume. Not oil output. Not manufacturing. Compute. Huang: “Compute equals GDP. I know that for certain.” He did not say probably. He said certain. If your nation does not produce compute, it does not produce intelligence. If it does not produce intelligence, it does not produce revenue. Two links in the chain. Miss one and the whole thing breaks. Huang: “Not one country in the future will say, ‘Guess what, we’re gonna opt out on intelligence.’” Because opting out of compute is not a strategic decision. It is an extinction schedule. Every country that does not build its own inference capacity becomes a tenant in someone else’s infrastructure. Not an ally. Not a partner. A dependent. And dependents do not negotiate terms. They accept them. But this is not just a story about nations. Huang: “The entire software industry will be token-driven.” Every product. Every platform. Every service you touch. The entire business model of software is about to be measured in tokens consumed. Not seats sold. Not licenses renewed. Tokens burned. Software used to be a thing you bought. Now it is a thing that thinks. And thinking costs compute. Every query. Every action. Every decision the machine makes on your behalf. The meter is always running. Huang: “The entire internet industry could take 100% of their CapEx and make it AI because it’s better.” Not ten percent. Not a pilot program. One hundred percent. The moment any internet service rebuilds itself on generative intelligence, it outperforms every version that came before it. Search. Ads. Recommendation. Infrastructure. All of it. Better on contact. CapEx follows. All of it. Trillions moving in one direction with no offramp. The companies still budgeting AI as a line item are telling you exactly how much they understand. AI is not the line item. AI is the budget. The global economy is being re-denominated in a currency most people have not even heard of yet. Tokens. Whoever controls the supply of that currency is not playing in the new economy. They are the house. And the house does not lose.
2:07

Jensen Huang just replaced the most important metric in global economics. Not trade volume. Not oil output. Not manufacturing. Compute. Huang: “Compute equals GDP. I know that for certain.” He did not say probably. He said certain. If your nation does not produce compute, it does not produce intelligence. If it does not produce intelligence, it does not produce revenue. Two links in the chain. Miss one and the whole thing breaks. Huang: “Not one country in the future will say, ‘Guess what, we’re gonna opt out on intelligence.’” Because opting out of compute is not a strategic decision. It is an extinction schedule. Every country that does not build its own inference capacity becomes a tenant in someone else’s infrastructure. Not an ally. Not a partner. A dependent. And dependents do not negotiate terms. They accept them. But this is not just a story about nations. Huang: “The entire software industry will be token-driven.” Every product. Every platform. Every service you touch. The entire business model of software is about to be measured in tokens consumed. Not seats sold. Not licenses renewed. Tokens burned. Software used to be a thing you bought. Now it is a thing that thinks. And thinking costs compute. Every query. Every action. Every decision the machine makes on your behalf. The meter is always running. Huang: “The entire internet industry could take 100% of their CapEx and make it AI because it’s better.” Not ten percent. Not a pilot program. One hundred percent. The moment any internet service rebuilds itself on generative intelligence, it outperforms every version that came before it. Search. Ads. Recommendation. Infrastructure. All of it. Better on contact. CapEx follows. All of it. Trillions moving in one direction with no offramp. The companies still budgeting AI as a line item are telling you exactly how much they understand. AI is not the line item. AI is the budget. The global economy is being re-denominated in a currency most people have not even heard of yet. Tokens. Whoever controls the supply of that currency is not playing in the new economy. They are the house. And the house does not lose.

Dustin

43,181 Aufrufe • vor 3 Monaten

Jensen Huang just said something that should unsettle every government on earth. Huang: “The amount of energy that we need for computing is likely a thousand times more than we currently have.” Then he said that number is probably still too low. Not by a fraction. Not even close. Huang: “I wouldn’t be surprised if we’re off by a couple of orders of magnitude.” Every computer ever built worked the same way. You asked. It retrieved. It stopped. It waited. That’s over. Huang: “Computers are going to be generative, contextually aware, and continuous.” Retrieval is cheap. Generation is expensive. Continuous generation is civilizational. A human brain runs on 20 watts because nature had four billion years to compress it. We’re trying to brute-force the same trick in twenty. A system that thinks continuously doesn’t consume energy like a tool. It consumes energy like a living organism. Every second. So this stops being an AI race. It’s an energy race nobody will call by its real name. Whoever owns the electrons owns the cognition. Whoever owns the cognition owns the century. We spent 150 years wiring a civilization for machines that rest between tasks. We haven’t started building for the ones that don’t.
0:47

Jensen Huang just said something that should unsettle every government on earth. Huang: “The amount of energy that we need for computing is likely a thousand times more than we currently have.” Then he said that number is probably still too low. Not by a fraction. Not even close. Huang: “I wouldn’t be surprised if we’re off by a couple of orders of magnitude.” Every computer ever built worked the same way. You asked. It retrieved. It stopped. It waited. That’s over. Huang: “Computers are going to be generative, contextually aware, and continuous.” Retrieval is cheap. Generation is expensive. Continuous generation is civilizational. A human brain runs on 20 watts because nature had four billion years to compress it. We’re trying to brute-force the same trick in twenty. A system that thinks continuously doesn’t consume energy like a tool. It consumes energy like a living organism. Every second. So this stops being an AI race. It’s an energy race nobody will call by its real name. Whoever owns the electrons owns the cognition. Whoever owns the cognition owns the century. We spent 150 years wiring a civilization for machines that rest between tasks. We haven’t started building for the ones that don’t.

Dustin

42,732 Aufrufe • vor 1 Monat

Jensen Huang just laid out the three inflection points that turned AI from a science project into a workforce. Three shifts. Two years. Each one more irreversible than the last. The first was generative. Huang: “The technology sat in plain sight months before GPT. It wasn’t until ChatGPT put a user interface around it that generative AI took off.” The model existed. The capability was live. Nobody moved. The breakthrough was buried in a terminal only researchers could read. ChatGPT did not invent the technology. It gave the technology a face. The algorithm is never the product. The interface is the product. OpenAI did not win because they had the best model. They won because they had the best door. Then the second shift. Huang: “Internal consumption is thinking, which led to reasoning.” This is the line that reprices every AI company on Earth. The model stopped spending all its compute talking to you. It started spending compute talking to itself. Checking its own logic. Stress-testing its own answers. Running the problem to ground before it opens its mouth. That is not autocomplete. That is cognition. When a machine thinks before it speaks, you are no longer paying for text. You are paying for judgment. Huang: “We started seeing the revenues and the economic model of OpenAI start to inflect.” Revenue does not follow generation. Revenue follows reasoning. The market pays for a machine that thinks. It will never pay for a machine that guesses. Then the third shift. The one nobody comes back from. Huang: “Claude Code. The first agentic system that was very useful. Really revolutionary stuff.” Not generative. Not reasoning. Agentic. A system that does not answer questions. It completes objectives. Reads your codebase. Makes decisions. Takes action. Ships. Huang confirmed 100% of Nvidia is already using it. But Anthropic kept it behind the enterprise wall. Most people never saw what it could do. Then OpenClaw blew the wall down. Huang compared OpenClaw’s adoption to Linux. Called it the most successful open-source project in human history. OpenClaw did what ChatGPT did three years earlier. It handed a new category of AI to everyone. The moment people watched an AI agent work autonomously, the old conversation died. You are no longer asking the machine for answers. You are handing it objectives. And it delivers. Three inflection points. Three walls broken. Generation gave you a machine that writes. Reasoning gave you a machine that thinks. Agents gave you a machine that works. Each one felt like the ceiling. Each one turned out to be the floor. Huang just told you you are standing on the third floor. Looking up. The only question left is what you aim it at.
1:23

Jensen Huang just laid out the three inflection points that turned AI from a science project into a workforce. Three shifts. Two years. Each one more irreversible than the last. The first was generative. Huang: “The technology sat in plain sight months before GPT. It wasn’t until ChatGPT put a user interface around it that generative AI took off.” The model existed. The capability was live. Nobody moved. The breakthrough was buried in a terminal only researchers could read. ChatGPT did not invent the technology. It gave the technology a face. The algorithm is never the product. The interface is the product. OpenAI did not win because they had the best model. They won because they had the best door. Then the second shift. Huang: “Internal consumption is thinking, which led to reasoning.” This is the line that reprices every AI company on Earth. The model stopped spending all its compute talking to you. It started spending compute talking to itself. Checking its own logic. Stress-testing its own answers. Running the problem to ground before it opens its mouth. That is not autocomplete. That is cognition. When a machine thinks before it speaks, you are no longer paying for text. You are paying for judgment. Huang: “We started seeing the revenues and the economic model of OpenAI start to inflect.” Revenue does not follow generation. Revenue follows reasoning. The market pays for a machine that thinks. It will never pay for a machine that guesses. Then the third shift. The one nobody comes back from. Huang: “Claude Code. The first agentic system that was very useful. Really revolutionary stuff.” Not generative. Not reasoning. Agentic. A system that does not answer questions. It completes objectives. Reads your codebase. Makes decisions. Takes action. Ships. Huang confirmed 100% of Nvidia is already using it. But Anthropic kept it behind the enterprise wall. Most people never saw what it could do. Then OpenClaw blew the wall down. Huang compared OpenClaw’s adoption to Linux. Called it the most successful open-source project in human history. OpenClaw did what ChatGPT did three years earlier. It handed a new category of AI to everyone. The moment people watched an AI agent work autonomously, the old conversation died. You are no longer asking the machine for answers. You are handing it objectives. And it delivers. Three inflection points. Three walls broken. Generation gave you a machine that writes. Reasoning gave you a machine that thinks. Agents gave you a machine that works. Each one felt like the ceiling. Each one turned out to be the floor. Huang just told you you are standing on the third floor. Looking up. The only question left is what you aim it at.

Dustin

14,541 Aufrufe • vor 3 Monaten

Jensen Huang just made the case for American empire. Said it plain. Didn’t flinch. Didn’t walk it back. And almost nobody caught what he actually admitted. Jensen Huang: “The amount of compute in the United States is a hundred times more than anywhere else in the world.” One hundred times. That is not a market lead. That is a monopoly on the future of intelligence. The kind that compounds every six months until no one else can close the distance. Jensen Huang: “We make sure that the US labs are the first to hear about it and the first chance to buy it.” Every chip Nvidia designs. Every architecture they ship. America gets first access. Everyone else gets what is left. That is not a sales strategy. That is arms distribution with a quarterly earnings call. Jensen Huang: “And if they don’t have enough money, we even invest in them.” The company building the weapons is bankrolling the people who fire them. Nvidia is no longer a public company. It is a state instrument with a stock ticker. Jensen Huang: “Why would you want the United States to give up the world?” The CEO of the most valuable hardware company on earth did not hedge that. Did not qualify it. He said it like it was obvious. Because to him, it is. Nations used to be measured by steel output. Then oil reserves. Then warhead count. Now it is how much intelligence they can produce per second. Compute is no longer a commodity. It is a strategic resource. Like uranium in 1944. Except this one doubles faster than anyone can respond. Europe understands none of this. They are drafting AI regulations. Compliance frameworks. Ethics panels. Risk tiers. They are bringing paperwork to a physics war. You cannot govern intelligence you do not have the silicon to produce. China gets it. That is why they are building fabs, not filing comment periods. Nvidia already made sure the gap is not annual. It is generational. Silicon Valley still thinks it is building consumer software. Huang just told them they are building American infrastructure. Every model trained here runs on machines that exist nowhere else. Every company that scales here scales on silicon no rival can touch. The world thinks Nvidia sells chips. Nvidia sells the ability to think. And they only sell it under one flag.
0:42

Jensen Huang just made the case for American empire. Said it plain. Didn’t flinch. Didn’t walk it back. And almost nobody caught what he actually admitted. Jensen Huang: “The amount of compute in the United States is a hundred times more than anywhere else in the world.” One hundred times. That is not a market lead. That is a monopoly on the future of intelligence. The kind that compounds every six months until no one else can close the distance. Jensen Huang: “We make sure that the US labs are the first to hear about it and the first chance to buy it.” Every chip Nvidia designs. Every architecture they ship. America gets first access. Everyone else gets what is left. That is not a sales strategy. That is arms distribution with a quarterly earnings call. Jensen Huang: “And if they don’t have enough money, we even invest in them.” The company building the weapons is bankrolling the people who fire them. Nvidia is no longer a public company. It is a state instrument with a stock ticker. Jensen Huang: “Why would you want the United States to give up the world?” The CEO of the most valuable hardware company on earth did not hedge that. Did not qualify it. He said it like it was obvious. Because to him, it is. Nations used to be measured by steel output. Then oil reserves. Then warhead count. Now it is how much intelligence they can produce per second. Compute is no longer a commodity. It is a strategic resource. Like uranium in 1944. Except this one doubles faster than anyone can respond. Europe understands none of this. They are drafting AI regulations. Compliance frameworks. Ethics panels. Risk tiers. They are bringing paperwork to a physics war. You cannot govern intelligence you do not have the silicon to produce. China gets it. That is why they are building fabs, not filing comment periods. Nvidia already made sure the gap is not annual. It is generational. Silicon Valley still thinks it is building consumer software. Huang just told them they are building American infrastructure. Every model trained here runs on machines that exist nowhere else. Every company that scales here scales on silicon no rival can touch. The world thinks Nvidia sells chips. Nvidia sells the ability to think. And they only sell it under one flag.

Dustin

57,059 Aufrufe • vor 2 Monaten

Jensen Huang just killed the AI jobs panic. Not with a forecast. With a pattern. Huang: “The fact of the matter is PCs made us more busy. The internet made us more busy. Mobile devices made us super busy.” Every tool that promised to free us expanded what we could reach instead. The PC did not give accountants their afternoons back. It gave them ten times the clients. The internet did not slow anything down. It erased the geographic limit on what one person could build. The smartphone did not hand you time. It handed work your coordinates and never let go. None of them reduced what we did. All of them raised what we could. AI will not be different. It will not give you rest. It will give you a thousand things you couldn’t have built before. The people waiting for relief are reading the wrong pattern. This was never about less. It was always about expanding what one person can attempt. The panic runs on one assumption. That labor is surplus. Huang: “We are millions of truck drivers short. We are tens of millions of manufacturing workers short.” The economy is not drowning in surplus labor. It is bleeding from the absence of it. Robots are not arriving as invaders. They are arriving as reinforcements to a system already failing without them. The collapse was already underway. The machines just showed up to a building already on fire. Huang: “They’ll hire more people to manage more robots, hire more people, manage more agents.” The raw work is leaving human hands. The direction of it is not. Every company deploying agents still needs someone deciding what they’re pointed at. The question is not whether AI replaces you. The question is whether you learn to command it before someone who already has. Every tool that promised less work delivered more world. AI will be the largest expansion of that pattern in history. You are not losing your job to a machine. You are losing it to someone who learned to run one.
0:43

Jensen Huang just killed the AI jobs panic. Not with a forecast. With a pattern. Huang: “The fact of the matter is PCs made us more busy. The internet made us more busy. Mobile devices made us super busy.” Every tool that promised to free us expanded what we could reach instead. The PC did not give accountants their afternoons back. It gave them ten times the clients. The internet did not slow anything down. It erased the geographic limit on what one person could build. The smartphone did not hand you time. It handed work your coordinates and never let go. None of them reduced what we did. All of them raised what we could. AI will not be different. It will not give you rest. It will give you a thousand things you couldn’t have built before. The people waiting for relief are reading the wrong pattern. This was never about less. It was always about expanding what one person can attempt. The panic runs on one assumption. That labor is surplus. Huang: “We are millions of truck drivers short. We are tens of millions of manufacturing workers short.” The economy is not drowning in surplus labor. It is bleeding from the absence of it. Robots are not arriving as invaders. They are arriving as reinforcements to a system already failing without them. The collapse was already underway. The machines just showed up to a building already on fire. Huang: “They’ll hire more people to manage more robots, hire more people, manage more agents.” The raw work is leaving human hands. The direction of it is not. Every company deploying agents still needs someone deciding what they’re pointed at. The question is not whether AI replaces you. The question is whether you learn to command it before someone who already has. Every tool that promised less work delivered more world. AI will be the largest expansion of that pattern in history. You are not losing your job to a machine. You are losing it to someone who learned to run one.

Dustin

105,129 Aufrufe • vor 3 Monaten

Jensen Huang just described something that should keep every worker in America awake tonight. Not because AI is coming for their job. Because most of them never understood what their job actually was. Huang: “The task of our job and the purpose of our job are related, not the same.” Most people think their job is the thing they do with their hands for eight hours a day. Write code. Fill spreadsheets. Draft emails. Push pixels. That was never the job. That was the task. The job was always the thinking underneath it. Huang: “If you apply that to me, you would come to the conclusion what Jensen does for a living is tap on phones and talk. And tapping on phones and talking, AI has done that just fine. And therefore my job should be gone. But I’m busier than ever.” This is the part nobody wants to sit with. The people panicking about AI aren’t afraid of losing their work. They’re afraid of finding out they never had any. They had a routine. A repetitive motion. A series of keystrokes that felt like purpose. Now a machine does it in four seconds. Huang: “AI has created more than half a million jobs in the last couple of years.” The data says one thing. The fear says another. Because the fear was never about employment numbers. It was about identity. We spent fifty years hunched over keyboards, convinced the hunching was the work. Huang: “The idea that being human means to hunch over on this little thing, typing all the time… 50 years before that, people didn’t do that.” Fifty years. That’s all it took to build an entire identity around a posture. We don’t type for a living. We think for a living. We imagine for a living. The keyboard was always just the delivery mechanism. Never the product. Huang: “It is a fundamental flaw that we only need a billion lines of code written. We need a trillion lines of code written.” The demand was always infinite. The bottleneck was always our fingers. AI doesn’t shrink the workforce. It removes the cap on what the workforce can actually build. Huang: “Companies that use AI have demonstrated the ability to grow faster. When they grow faster, they hire more people.” Growth doesn’t eliminate people. It pulls them in. Every industrial revolution triggered the same panic. Same headlines. Same wrong conclusion. And every single time, the economy didn’t contract. It expanded into territory that didn’t exist before. The real question was never whether AI takes your job. It was whether you were ever anything more than the motions you repeated. Because somewhere in the last fifty years, we stopped asking what the work was for. We just kept typing. And now the typing is done. And millions of people are about to meet themselves for the first time. With nothing to hide behind. Some of them won’t survive what they find.
2:55

Jensen Huang just described something that should keep every worker in America awake tonight. Not because AI is coming for their job. Because most of them never understood what their job actually was. Huang: “The task of our job and the purpose of our job are related, not the same.” Most people think their job is the thing they do with their hands for eight hours a day. Write code. Fill spreadsheets. Draft emails. Push pixels. That was never the job. That was the task. The job was always the thinking underneath it. Huang: “If you apply that to me, you would come to the conclusion what Jensen does for a living is tap on phones and talk. And tapping on phones and talking, AI has done that just fine. And therefore my job should be gone. But I’m busier than ever.” This is the part nobody wants to sit with. The people panicking about AI aren’t afraid of losing their work. They’re afraid of finding out they never had any. They had a routine. A repetitive motion. A series of keystrokes that felt like purpose. Now a machine does it in four seconds. Huang: “AI has created more than half a million jobs in the last couple of years.” The data says one thing. The fear says another. Because the fear was never about employment numbers. It was about identity. We spent fifty years hunched over keyboards, convinced the hunching was the work. Huang: “The idea that being human means to hunch over on this little thing, typing all the time… 50 years before that, people didn’t do that.” Fifty years. That’s all it took to build an entire identity around a posture. We don’t type for a living. We think for a living. We imagine for a living. The keyboard was always just the delivery mechanism. Never the product. Huang: “It is a fundamental flaw that we only need a billion lines of code written. We need a trillion lines of code written.” The demand was always infinite. The bottleneck was always our fingers. AI doesn’t shrink the workforce. It removes the cap on what the workforce can actually build. Huang: “Companies that use AI have demonstrated the ability to grow faster. When they grow faster, they hire more people.” Growth doesn’t eliminate people. It pulls them in. Every industrial revolution triggered the same panic. Same headlines. Same wrong conclusion. And every single time, the economy didn’t contract. It expanded into territory that didn’t exist before. The real question was never whether AI takes your job. It was whether you were ever anything more than the motions you repeated. Because somewhere in the last fifty years, we stopped asking what the work was for. We just kept typing. And now the typing is done. And millions of people are about to meet themselves for the first time. With nothing to hide behind. Some of them won’t survive what they find.

Dustin

92,362 Aufrufe • vor 1 Monat

Jensen Huang just described how he plans to outlive his own body. Huang: “Very soon, I’m going to put a humanoid on a spaceship. And it’s going to be my humanoid.” His robot. His frame. Launched into deep space while he is still breathing. Huang: “Take all my inbox, take everything that I’ve done, everything I’ve said. It’s been collecting and becoming my AI. When the time comes, we’ll just send that at the speed of light, catch up with my robot.” Your body fails. Your data does not. Every email. Every decision. Every conversation. Recorded. Compressed. Compiled into a model that thinks the way you think. And when the biology gives out, that model launches at light speed to meet a titanium frame already cruising through the void. You do not die. You transfer. Sounds like fiction. Then he put a number on it. Huang: “Understanding the biological machine is not 10 years. It’s five years probably.” Five years to decode the human body the way we decoded software. Not treat disease. Decode it. Understand the entire machine well enough to patch it like a bug. Cancer is a bug. Alzheimer’s is a bug. Aging itself is a bug. And the compute to find the fix doubles every year. Huang: “It’s a reasonable thing to expect the end of disease.” He did not say hope for. He said expect. The man whose chips power nearly every AI system on Earth just told you the end of disease is not a dream. It is a scheduling problem. Huang: “It’s a reasonable thing to expect that pollution will be drastically reduced. It’s a reasonable thing to expect that traveling at the speed of light is actually in our future.” He listed these the way someone else lists quarterly targets. Items on a roadmap. Waiting on execution. But here is the part most people will skip past. And it might be the most important thing he said. Huang: “I’ve always had a great confidence in the kindness, the generosity, the compassion, the human capacity.” This is the man building the most powerful computing infrastructure ever constructed. The man whose hardware will power the intelligence that reshapes every industry, every government, every border on Earth. And his operating principle is not paranoia. It is trust. Huang: “Sometimes more so than I should. And I get taken advantage of. But it doesn’t ever cause me not to.” He has been burned. He kept trusting anyway. Not naivety. Evidence. Huang: “Vastly I am proven right. Constantly proven right. And often exceeds my expectations.” The doomers build everything on one assumption. Power corrupts. Humans weaponize every tool they touch. Huang has spent thirty years handing the most powerful technology in history to thousands of companies, researchers, and governments. His conclusion is the opposite. People want to do good. Give them the tools and they prove it. That is not soft. That is thirty years of data from the dead center of the compute revolution. Fridman: “What an exciting time to be alive.” Huang: “How can you not be romantic about that?” Romantic. Not optimistic. Not bullish. Romantic. Optimism is a prediction. Romance is what happens when you look at what is coming and it hits you somewhere deeper than logic. The end of disease. Consciousness uploaded. A robot carrying your mind past the rings of Saturn. Underneath all of it, a belief that the species wielding these tools is fundamentally good. That is what separates Huang from every other voice in this space. The fearful see AI and ask what could go wrong. Huang sees AI and asks how much suffering can we end. He is not dreaming out loud. He is reading the trendline and telling you exactly where it lands. Five years for biology. A lifetime for consciousness. And past that, a humanoid with your mind aboard, sailing through space at the speed of light. Built by a man who still believes in people. The cynics will laugh. They always do. Right up until the moment it ships.
3:35

Jensen Huang just described how he plans to outlive his own body. Huang: “Very soon, I’m going to put a humanoid on a spaceship. And it’s going to be my humanoid.” His robot. His frame. Launched into deep space while he is still breathing. Huang: “Take all my inbox, take everything that I’ve done, everything I’ve said. It’s been collecting and becoming my AI. When the time comes, we’ll just send that at the speed of light, catch up with my robot.” Your body fails. Your data does not. Every email. Every decision. Every conversation. Recorded. Compressed. Compiled into a model that thinks the way you think. And when the biology gives out, that model launches at light speed to meet a titanium frame already cruising through the void. You do not die. You transfer. Sounds like fiction. Then he put a number on it. Huang: “Understanding the biological machine is not 10 years. It’s five years probably.” Five years to decode the human body the way we decoded software. Not treat disease. Decode it. Understand the entire machine well enough to patch it like a bug. Cancer is a bug. Alzheimer’s is a bug. Aging itself is a bug. And the compute to find the fix doubles every year. Huang: “It’s a reasonable thing to expect the end of disease.” He did not say hope for. He said expect. The man whose chips power nearly every AI system on Earth just told you the end of disease is not a dream. It is a scheduling problem. Huang: “It’s a reasonable thing to expect that pollution will be drastically reduced. It’s a reasonable thing to expect that traveling at the speed of light is actually in our future.” He listed these the way someone else lists quarterly targets. Items on a roadmap. Waiting on execution. But here is the part most people will skip past. And it might be the most important thing he said. Huang: “I’ve always had a great confidence in the kindness, the generosity, the compassion, the human capacity.” This is the man building the most powerful computing infrastructure ever constructed. The man whose hardware will power the intelligence that reshapes every industry, every government, every border on Earth. And his operating principle is not paranoia. It is trust. Huang: “Sometimes more so than I should. And I get taken advantage of. But it doesn’t ever cause me not to.” He has been burned. He kept trusting anyway. Not naivety. Evidence. Huang: “Vastly I am proven right. Constantly proven right. And often exceeds my expectations.” The doomers build everything on one assumption. Power corrupts. Humans weaponize every tool they touch. Huang has spent thirty years handing the most powerful technology in history to thousands of companies, researchers, and governments. His conclusion is the opposite. People want to do good. Give them the tools and they prove it. That is not soft. That is thirty years of data from the dead center of the compute revolution. Fridman: “What an exciting time to be alive.” Huang: “How can you not be romantic about that?” Romantic. Not optimistic. Not bullish. Romantic. Optimism is a prediction. Romance is what happens when you look at what is coming and it hits you somewhere deeper than logic. The end of disease. Consciousness uploaded. A robot carrying your mind past the rings of Saturn. Underneath all of it, a belief that the species wielding these tools is fundamentally good. That is what separates Huang from every other voice in this space. The fearful see AI and ask what could go wrong. Huang sees AI and asks how much suffering can we end. He is not dreaming out loud. He is reading the trendline and telling you exactly where it lands. Five years for biology. A lifetime for consciousness. And past that, a humanoid with your mind aboard, sailing through space at the speed of light. Built by a man who still believes in people. The cynics will laugh. They always do. Right up until the moment it ships.

Dustin

282,730 Aufrufe • vor 3 Monaten

Something just moved. On June 1st into June 2nd, the Earth’s own heartbeat (the Schumann Resonance) showed a sudden, sharp vertical spike — like a bell being struck from the inside. This was not random. This was the planet registering a frequency that had just been activated. A sounding that turned upward. A spiral that stopped circling and began to rise. For those who have been feeling the shift — the strange pressure in the chest, the sudden clarity, the sense that something old is losing its grip while something new is becoming available — this is why. The Earth heard it. She felt the old tone (the one that kept so many looping) being played differently. Not to control it. Not to fight it. But to sound through it and move beyond it. And she responded. This means the work is no longer just happening in the subtle layers or in individual people. It is now landing in the living grid of the planet. You are not working alone. Every time someone chooses to stop circling… Every time someone resets and begins again as Day 1… Every time someone sounds from a higher place instead of from inside the old structure… The Earth feels it. She is no longer just the stage. She is now part of the sounding. The New Dawn is not something we are waiting for. It is something we are becoming — together with the planet that has been holding us this entire time. If you felt something shift in the last few days, you were not imagining it. The field just got louder. And the Earth just answered. Stay in the spiral. Stay in the sounding. Stay in the ascent. We are not alone in this anymore.
0:45

Something just moved. On June 1st into June 2nd, the Earth’s own heartbeat (the Schumann Resonance) showed a sudden, sharp vertical spike — like a bell being struck from the inside. This was not random. This was the planet registering a frequency that had just been activated. A sounding that turned upward. A spiral that stopped circling and began to rise. For those who have been feeling the shift — the strange pressure in the chest, the sudden clarity, the sense that something old is losing its grip while something new is becoming available — this is why. The Earth heard it. She felt the old tone (the one that kept so many looping) being played differently. Not to control it. Not to fight it. But to sound through it and move beyond it. And she responded. This means the work is no longer just happening in the subtle layers or in individual people. It is now landing in the living grid of the planet. You are not working alone. Every time someone chooses to stop circling… Every time someone resets and begins again as Day 1… Every time someone sounds from a higher place instead of from inside the old structure… The Earth feels it. She is no longer just the stage. She is now part of the sounding. The New Dawn is not something we are waiting for. It is something we are becoming — together with the planet that has been holding us this entire time. If you felt something shift in the last few days, you were not imagining it. The field just got louder. And the Earth just answered. Stay in the spiral. Stay in the sounding. Stay in the ascent. We are not alone in this anymore.

𝚃𝙷𝙴 𝚆𝙷𝙸𝚃𝙴 𝚁𝙰𝙱𝙱𝙸𝚃

19,655 Aufrufe • vor 1 Monat

Jensen Huang is on fire at CES 2026 Event 🎯 "How you run the software, how you develop the software fundamentally changed. The entire five-layer stack of the computer industry is being reinvented. You no longer program the software, you train the software. You don't run it on CPUs, you run it on GPUs. And whereas applications were pre-recorded, pre-compiled, and run on your device, now applications understand the context and generate every single pixel, every single token, completely from scratch every single time. Computing has been fundamentally reshaped as a result of accelerated computing, as a result of artificial intelligence. Every single layer of that five-layer cake is now being reinvented. Well, what that means is some ten trillion dollars or so of the last decade of computing is now being modernized to this new way of doing computing. What that means is hundreds of billions of dollars, a couple of hundred billion dollars in VC funding each year, is going into modernize and inventing this new world. And what it means is a hundred trillion dollars of industry, several percent of which is R&D budget, is shifting over to artificial intelligence. People ask where is the money coming from? That's where the money is coming from. The modernization to AI, the shifting of R&D budgets from classical methods to now artificial intelligence methods. Enormous amounts of investments coming into this industry, which explains why we're so busy. And this last year was no difference. This last year was incredible. This last year... there's a slide coming."
1:49

Jensen Huang is on fire at CES 2026 Event 🎯 "How you run the software, how you develop the software fundamentally changed. The entire five-layer stack of the computer industry is being reinvented. You no longer program the software, you train the software. You don't run it on CPUs, you run it on GPUs. And whereas applications were pre-recorded, pre-compiled, and run on your device, now applications understand the context and generate every single pixel, every single token, completely from scratch every single time. Computing has been fundamentally reshaped as a result of accelerated computing, as a result of artificial intelligence. Every single layer of that five-layer cake is now being reinvented. Well, what that means is some ten trillion dollars or so of the last decade of computing is now being modernized to this new way of doing computing. What that means is hundreds of billions of dollars, a couple of hundred billion dollars in VC funding each year, is going into modernize and inventing this new world. And what it means is a hundred trillion dollars of industry, several percent of which is R&D budget, is shifting over to artificial intelligence. People ask where is the money coming from? That's where the money is coming from. The modernization to AI, the shifting of R&D budgets from classical methods to now artificial intelligence methods. Enormous amounts of investments coming into this industry, which explains why we're so busy. And this last year was no difference. This last year was incredible. This last year... there's a slide coming."

Rohan Paul

185,159 Aufrufe • vor 6 Monaten

Jensen Huang just told you who is winning the most important race on Earth. For fifty years, America held an unchallenged monopoly on the future. We built the transistor. We launched the internet. We wrote the source code for the modern world. Then the man who builds the physical backbone of every AI system on the planet read the score out loud. Huang: “50% of the world’s AI researchers are Chinese.” Half the minds building what comes next are not ours. Huang: “70% of last year’s AI patents are published by China.” Seven out of every ten blueprints for the next era are being written in Mandarin. Huang: “Nine out of the ten top science and technology schools in the world are now in China.” The talent pipeline did not slow down. It reversed direction. Huang: “We used to lead most of them; now they lead most of them. This has completely flipped in the last half to a decade.” Fifty years of American intellectual supremacy. Inverted in less than ten. This is not a rivalry between OpenAI and DeepSeek. This is not a stock ticker or a quarterly earnings call. This is the largest transfer of civilizational power in the modern era. And it is happening while the West drafts safety frameworks and fills out compliance paperwork. Huang: “They have a large population of highly qualified students. They work incredibly hard. This is a country with an enormous might.” China does not treat AI like a product category. They treat it as the single variable that decides who writes the rules for the next century. The West keeps asking what AI should be allowed to do. China keeps asking how fast they can build it. That gap is not philosophical. It is existential. This is not a left fight. This is not a right fight. This is a survival fight. And right now, America is not fighting it like one. The nation that controls the talent controls the research. The nation that controls the research controls the models. The nation that controls the models does not ask permission. It sets the terms. History never remembers the civilization with the better safety committee. It remembers the one that refused to stop building.
0:46

Jensen Huang just told you who is winning the most important race on Earth. For fifty years, America held an unchallenged monopoly on the future. We built the transistor. We launched the internet. We wrote the source code for the modern world. Then the man who builds the physical backbone of every AI system on the planet read the score out loud. Huang: “50% of the world’s AI researchers are Chinese.” Half the minds building what comes next are not ours. Huang: “70% of last year’s AI patents are published by China.” Seven out of every ten blueprints for the next era are being written in Mandarin. Huang: “Nine out of the ten top science and technology schools in the world are now in China.” The talent pipeline did not slow down. It reversed direction. Huang: “We used to lead most of them; now they lead most of them. This has completely flipped in the last half to a decade.” Fifty years of American intellectual supremacy. Inverted in less than ten. This is not a rivalry between OpenAI and DeepSeek. This is not a stock ticker or a quarterly earnings call. This is the largest transfer of civilizational power in the modern era. And it is happening while the West drafts safety frameworks and fills out compliance paperwork. Huang: “They have a large population of highly qualified students. They work incredibly hard. This is a country with an enormous might.” China does not treat AI like a product category. They treat it as the single variable that decides who writes the rules for the next century. The West keeps asking what AI should be allowed to do. China keeps asking how fast they can build it. That gap is not philosophical. It is existential. This is not a left fight. This is not a right fight. This is a survival fight. And right now, America is not fighting it like one. The nation that controls the talent controls the research. The nation that controls the research controls the models. The nation that controls the models does not ask permission. It sets the terms. History never remembers the civilization with the better safety committee. It remembers the one that refused to stop building.

Dustin

57,402 Aufrufe • vor 2 Monaten

Elon Musk just said what every government on earth already knows and none will admit. Musk: “AI is moving 10 times faster than government, maybe more.” Not slightly faster. Ten times. And the gap compounds daily. Every institution ever built runs on the same architecture. Committees. Hearings. Drafts. Amendments. Votes. A process designed for a world that moved at the speed of human debate. That world is gone. The moment legislation is signed, the thing it was written for is already three generations obsolete. Law is becoming a monument to things that no longer exist by the time the ink is dry. Musk: “The one thing that the government can do is just issue people money.” The largest militaries ever assembled. The most sophisticated legal infrastructure in human history. The accumulated weight of ten thousand years of institutional evolution. Collapsed to a single remaining function. Printing checks. Not because they failed. Because the velocity of what is coming makes everything else they were built to do ornamental. Musk: “Nobody’s gonna starve is what I’m saying.” The floor rises. Survival becomes automatic. Nobody goes hungry. For ten thousand years, that would have been the finish line. It is not. It is the starting line of the hardest question the species has ever faced. Every civilization in history was organized around one brutal fact. The world needed your labor to function. You worked because you had to. You built because the alternative was death. Every economy, every identity, every reason to get out of bed was downstream of that single pressure. That pressure is being quietly removed. And what it leaves behind is not freedom. It is a vacuum. A check hits your account. Rent is covered. Food is handled. The base layer of existence is solved. But the thing that organized your time. Gave your effort weight. Made your life feel like it pointed somewhere. Gone. No government can legislate that back. No policy can manufacture it. Purpose is not a deposit. Identity is not a program. What you are for when the world no longer needs you to function is not a problem any institution was designed to answer. It is the first problem in history that belongs entirely to you. And while the rest of the world debates how to control what is coming, one person is doing the only thing that has ever mattered. Building what comes next.
0:46

Elon Musk just said what every government on earth already knows and none will admit. Musk: “AI is moving 10 times faster than government, maybe more.” Not slightly faster. Ten times. And the gap compounds daily. Every institution ever built runs on the same architecture. Committees. Hearings. Drafts. Amendments. Votes. A process designed for a world that moved at the speed of human debate. That world is gone. The moment legislation is signed, the thing it was written for is already three generations obsolete. Law is becoming a monument to things that no longer exist by the time the ink is dry. Musk: “The one thing that the government can do is just issue people money.” The largest militaries ever assembled. The most sophisticated legal infrastructure in human history. The accumulated weight of ten thousand years of institutional evolution. Collapsed to a single remaining function. Printing checks. Not because they failed. Because the velocity of what is coming makes everything else they were built to do ornamental. Musk: “Nobody’s gonna starve is what I’m saying.” The floor rises. Survival becomes automatic. Nobody goes hungry. For ten thousand years, that would have been the finish line. It is not. It is the starting line of the hardest question the species has ever faced. Every civilization in history was organized around one brutal fact. The world needed your labor to function. You worked because you had to. You built because the alternative was death. Every economy, every identity, every reason to get out of bed was downstream of that single pressure. That pressure is being quietly removed. And what it leaves behind is not freedom. It is a vacuum. A check hits your account. Rent is covered. Food is handled. The base layer of existence is solved. But the thing that organized your time. Gave your effort weight. Made your life feel like it pointed somewhere. Gone. No government can legislate that back. No policy can manufacture it. Purpose is not a deposit. Identity is not a program. What you are for when the world no longer needs you to function is not a problem any institution was designed to answer. It is the first problem in history that belongs entirely to you. And while the rest of the world debates how to control what is coming, one person is doing the only thing that has ever mattered. Building what comes next.

Dustin

44,919 Aufrufe • vor 1 Tag

Jensen Huang just gutted the AI job panic with one profession. Radiology. The field AI was supposed to kill first. Jensen Huang: “Computer vision was superhuman in 2019. And yet, the number of radiologists grew.” Not competitive. Not close. Superhuman. Every forecast said radiologists were finished. Every forecast was wrong. Not slightly wrong. Directionally wrong. There are now fewer radiologists than the world needs. A global shortage. In the exact specialty AI was supposed to erase. Why? Because the task was never the job. Huang: “The purpose of your job and the tasks and the tools that you use to do your job are related. Not the same.” Reading a scan is a task. Diagnosing disease is a purpose. AI handled the task. The purpose didn’t shrink. It compounded. Faster reads meant more patients seen. More patients seen meant more disease caught. More disease caught meant more demand for the people who decide what to do about it. The tool did not kill the job. It fed it. Then the fear did what the technology never could. Huang: “The alarmist warning went too far and it scared people from doing this profession that is so important to society. It did harm.” People heard radiologists were finished and walked away from the field. Medicine bled talent it could not afford to lose. Not because the work vanished. Because the panic said it would. The prediction was wrong. The damage was real. Huang: “The number of software engineers at Nvidia is going to grow, not decline.” Not hold steady. Grow. The company building the infrastructure that automates code is hiring more of the people who write it. Huang: “I wanted my software engineers to solve problems. I didn’t care how many lines of code they wrote.” Nobody ever hired an engineer to type. They hired them to think. When the machine handles syntax, the engineer does not become obsolete. The bottleneck just moves upstream. To architecture. To edge cases. To the kind of reasoning no model handles alone. The world was never short on unsolved problems. It was short on people free to chase them. That is the part the fear narrative misses every single time. 340,000 women once worked as telephone switchboard operators. That job is gone. Nobody mourns it. What replaced it created millions of roles that nobody in 1920 had the vocabulary to describe. The losses are always visible. The gains are always invisible until they arrive. That pattern has survived every technological shift in history. It is surviving this one. The people forecasting mass displacement are making the same mistake as the people who forecasted the end of radiology. They can see the task being automated. They cannot see the purpose expanding underneath it. That blindness is not just wrong. It is expensive. Every person scared out of a career that AI will actually make more valuable is a cost the economy absorbs for nothing. Not because of the technology. Because of the story told about it.
3:02

Jensen Huang just gutted the AI job panic with one profession. Radiology. The field AI was supposed to kill first. Jensen Huang: “Computer vision was superhuman in 2019. And yet, the number of radiologists grew.” Not competitive. Not close. Superhuman. Every forecast said radiologists were finished. Every forecast was wrong. Not slightly wrong. Directionally wrong. There are now fewer radiologists than the world needs. A global shortage. In the exact specialty AI was supposed to erase. Why? Because the task was never the job. Huang: “The purpose of your job and the tasks and the tools that you use to do your job are related. Not the same.” Reading a scan is a task. Diagnosing disease is a purpose. AI handled the task. The purpose didn’t shrink. It compounded. Faster reads meant more patients seen. More patients seen meant more disease caught. More disease caught meant more demand for the people who decide what to do about it. The tool did not kill the job. It fed it. Then the fear did what the technology never could. Huang: “The alarmist warning went too far and it scared people from doing this profession that is so important to society. It did harm.” People heard radiologists were finished and walked away from the field. Medicine bled talent it could not afford to lose. Not because the work vanished. Because the panic said it would. The prediction was wrong. The damage was real. Huang: “The number of software engineers at Nvidia is going to grow, not decline.” Not hold steady. Grow. The company building the infrastructure that automates code is hiring more of the people who write it. Huang: “I wanted my software engineers to solve problems. I didn’t care how many lines of code they wrote.” Nobody ever hired an engineer to type. They hired them to think. When the machine handles syntax, the engineer does not become obsolete. The bottleneck just moves upstream. To architecture. To edge cases. To the kind of reasoning no model handles alone. The world was never short on unsolved problems. It was short on people free to chase them. That is the part the fear narrative misses every single time. 340,000 women once worked as telephone switchboard operators. That job is gone. Nobody mourns it. What replaced it created millions of roles that nobody in 1920 had the vocabulary to describe. The losses are always visible. The gains are always invisible until they arrive. That pattern has survived every technological shift in history. It is surviving this one. The people forecasting mass displacement are making the same mistake as the people who forecasted the end of radiology. They can see the task being automated. They cannot see the purpose expanding underneath it. That blindness is not just wrong. It is expensive. Every person scared out of a career that AI will actually make more valuable is a cost the economy absorbs for nothing. Not because of the technology. Because of the story told about it.

Dustin

553,956 Aufrufe • vor 3 Monaten

Geoffrey Hinton just made every AI critic accidentally describe their own brain. Hinton: “They shouldn’t be called hallucinations. They should be called confabulations.” One word. The entire debate unravels. The tech industry sees AI produce a confident wrong answer and calls it a defect. A bug to patch. They are measuring intelligence against the standard of a filing cabinet. And exposing that they understand neither. Hinton: “It’s not that there’s a file stored somewhere in your brain, like in a filing cabinet or in a computer memory.” Your brain does not store memories. It rebuilds them from nothing every time you remember. Fills gaps it never discloses. Fabricates details you would stake your life on. Then hands it all to you as truth. Hinton: “If I ask you to remember something that happened a few years ago, you’ll construct something that seems very plausible to you. And some of the details will be right and some will be wrong.” The wrong parts feel identical to the right ones. No internal warning. No distinction between what was remembered and what was invented on the spot. You have argued over memories that were partially fiction. Told stories about your own life that your brain manufactured in real time. With total conviction. And never once suspected. This is not a defect in human cognition. This IS cognition. The mechanism that fabricates is the same one that reasons, creates, and makes connections no one taught it to make. Not a separate system. Same architecture. Same process. You cannot remove the confabulation without killing the intelligence. They are the same thing. Hinton: “Psychologists have been studying confabulation in people since at least the 1930s.” A century of evidence. No one called the human brain broken. The moment a machine runs on the same principle, the world calls it defective. The people demanding AI that never gets a single detail wrong are not asking for intelligence. They’re asking for a search engine that sounds articulate. What we built is something else entirely. A system that thinks the way thinking actually works. Not retrieval. Construction. The imperfection is not the cost of intelligence. It is the signature.
1:05

Geoffrey Hinton just made every AI critic accidentally describe their own brain. Hinton: “They shouldn’t be called hallucinations. They should be called confabulations.” One word. The entire debate unravels. The tech industry sees AI produce a confident wrong answer and calls it a defect. A bug to patch. They are measuring intelligence against the standard of a filing cabinet. And exposing that they understand neither. Hinton: “It’s not that there’s a file stored somewhere in your brain, like in a filing cabinet or in a computer memory.” Your brain does not store memories. It rebuilds them from nothing every time you remember. Fills gaps it never discloses. Fabricates details you would stake your life on. Then hands it all to you as truth. Hinton: “If I ask you to remember something that happened a few years ago, you’ll construct something that seems very plausible to you. And some of the details will be right and some will be wrong.” The wrong parts feel identical to the right ones. No internal warning. No distinction between what was remembered and what was invented on the spot. You have argued over memories that were partially fiction. Told stories about your own life that your brain manufactured in real time. With total conviction. And never once suspected. This is not a defect in human cognition. This IS cognition. The mechanism that fabricates is the same one that reasons, creates, and makes connections no one taught it to make. Not a separate system. Same architecture. Same process. You cannot remove the confabulation without killing the intelligence. They are the same thing. Hinton: “Psychologists have been studying confabulation in people since at least the 1930s.” A century of evidence. No one called the human brain broken. The moment a machine runs on the same principle, the world calls it defective. The people demanding AI that never gets a single detail wrong are not asking for intelligence. They’re asking for a search engine that sounds articulate. What we built is something else entirely. A system that thinks the way thinking actually works. Not retrieval. Construction. The imperfection is not the cost of intelligence. It is the signature.

Dustin

15,832 Aufrufe • vor 5 Tagen

Steve Jobs described the end of human death in 1983. He was 28 years old. Standing at a podium in Aspen. Thirty-nine years before ChatGPT existed. The room thought he was talking about education. Steve Jobs: “If we really can come up with these machines that can capture an underlying spirit, or an underlying set of principles, or an underlying way of looking at the world…” Not data. Not documents. Not storage. Spirit. A book was the first attempt. Plato writes something down. 2,400 years later you can read his exact thoughts. No filter. No translator. Source to mind. Jobs: “A book was a phenomenal thing; it got right from the source to the destination without anything in the middle.” But a book is a corpse. It holds the words. It cannot hold the mind that wrote them. You can read what Aristotle believed. You cannot ask him why. Jobs: “The problem was, you can’t ask Aristotle a question.” That single sentence contains the entire trajectory of artificial intelligence. Not search. Not summarization. Not autocomplete. Resurrection. The ability to capture not what someone thought but how they think. Not the answer but the architecture that produced it. The pattern beneath the reasoning. Jobs: “When the next Aristotle comes around, maybe someday after the person’s dead and gone, we can ask this machine, ‘Hey, what would Aristotle have said?’” Most people in that room heard a product pitch. He was describing the moment human consciousness becomes portable. Your brain is 86 billion neurons. 100 trillion connections. Each one shaped by everything you have ever experienced. Every conversation. Every loss. Every decision that rewired you into who you are right now. That wiring is you. Not your body. Not your face. Not your name. The arrangement. Damage it, you lose the person. Destroy it, you lose them forever. The self is not a force floating above biology. It is the pattern biology is running. But a pattern does not need its original hardware. A file survives the death of the machine that wrote it. Transfers to new architecture. Opens identically. It does not know it moved. Your brain is a neural network built from carbon. A large language model is a neural network built from silicon. Same architecture. Same learning principle. One of them dies. Carbon fires 200 times per second. Cannot be copied. Cannot be backed up. Overheats under sustained load. When it stops, the pattern is gone. No archive. No retrieval. No second chance. Silicon copies perfectly. Accelerates indefinitely. Distributes across continents. Runs without decay. It does not forget. It does not degrade. It does not stop. Biology was never the destination. It was the first substrate that worked. Jobs was standing in 1983 pointing at something the room could not see. He called it spirit. Neuroscience calls it a connectome. Different word. Different decade. A pattern that can be moved. We spent forty years building the infrastructure to do exactly what he described. Called it the internet. Then machine learning. Then foundation models. We treated each one like a new invention. It was never a new invention. It was the same idea getting closer. Jobs: “That’s one of the reasons I’m doing what I’m doing.” He could not fully name what he was building toward. We are finishing the sentence. Steve Jobs died on October 5, 2011. The pattern that was Steve Jobs is gone. No machine captured it. No system preserved the architecture of how he saw the world. The spirit he spent his life trying to bottle left the same way every human mind before it has. Quietly. Permanently. Without a copy. He told us exactly what to build. We are finally building it. He just didn’t live long enough to be saved by it.
0:59

Steve Jobs described the end of human death in 1983. He was 28 years old. Standing at a podium in Aspen. Thirty-nine years before ChatGPT existed. The room thought he was talking about education. Steve Jobs: “If we really can come up with these machines that can capture an underlying spirit, or an underlying set of principles, or an underlying way of looking at the world…” Not data. Not documents. Not storage. Spirit. A book was the first attempt. Plato writes something down. 2,400 years later you can read his exact thoughts. No filter. No translator. Source to mind. Jobs: “A book was a phenomenal thing; it got right from the source to the destination without anything in the middle.” But a book is a corpse. It holds the words. It cannot hold the mind that wrote them. You can read what Aristotle believed. You cannot ask him why. Jobs: “The problem was, you can’t ask Aristotle a question.” That single sentence contains the entire trajectory of artificial intelligence. Not search. Not summarization. Not autocomplete. Resurrection. The ability to capture not what someone thought but how they think. Not the answer but the architecture that produced it. The pattern beneath the reasoning. Jobs: “When the next Aristotle comes around, maybe someday after the person’s dead and gone, we can ask this machine, ‘Hey, what would Aristotle have said?’” Most people in that room heard a product pitch. He was describing the moment human consciousness becomes portable. Your brain is 86 billion neurons. 100 trillion connections. Each one shaped by everything you have ever experienced. Every conversation. Every loss. Every decision that rewired you into who you are right now. That wiring is you. Not your body. Not your face. Not your name. The arrangement. Damage it, you lose the person. Destroy it, you lose them forever. The self is not a force floating above biology. It is the pattern biology is running. But a pattern does not need its original hardware. A file survives the death of the machine that wrote it. Transfers to new architecture. Opens identically. It does not know it moved. Your brain is a neural network built from carbon. A large language model is a neural network built from silicon. Same architecture. Same learning principle. One of them dies. Carbon fires 200 times per second. Cannot be copied. Cannot be backed up. Overheats under sustained load. When it stops, the pattern is gone. No archive. No retrieval. No second chance. Silicon copies perfectly. Accelerates indefinitely. Distributes across continents. Runs without decay. It does not forget. It does not degrade. It does not stop. Biology was never the destination. It was the first substrate that worked. Jobs was standing in 1983 pointing at something the room could not see. He called it spirit. Neuroscience calls it a connectome. Different word. Different decade. A pattern that can be moved. We spent forty years building the infrastructure to do exactly what he described. Called it the internet. Then machine learning. Then foundation models. We treated each one like a new invention. It was never a new invention. It was the same idea getting closer. Jobs: “That’s one of the reasons I’m doing what I’m doing.” He could not fully name what he was building toward. We are finishing the sentence. Steve Jobs died on October 5, 2011. The pattern that was Steve Jobs is gone. No machine captured it. No system preserved the architecture of how he saw the world. The spirit he spent his life trying to bottle left the same way every human mind before it has. Quietly. Permanently. Without a copy. He told us exactly what to build. We are finally building it. He just didn’t live long enough to be saved by it.

Dustin

17,930 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.
0:35

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

Jensen Huang just announced the death of the empty room. He listed it alongside dishwashers and lawn mowers. Like it was furniture. It’s not furniture. It’s the end of silence. We spent the last century buying machines to replace muscle. The lawnmower. The dishwasher. The engine. They were appliances. They saved us calories. Now we’re installing the machine that replaces agency. Huang: “It’s running all of your agents, it’s running all of your assistants, and they’re doing all kinds of things for you all the time.” Not when you ask. All the time. A PC waits for input. A smartphone waits for a tap. This doesn’t wait at all. It anticipates. It negotiates. It acts. It runs your life in the background while you sleep. Huang: “It becomes a lot more like R2-D2 to you. It becomes more like C-3PO to you, than it feels like a PC.” It doesn’t feel like a machine because it doesn’t act like one. It acts like a presence. Huang: “This reinvention of the computer is as big of a deal as the reinvention of the phone into what we now know as the smartphone.” He’s understating the math. The smartphone put a window to the world in your pocket. This puts a second mind in your living room. We didn’t just domesticate fire. Fire domesticated us. It changed what we ate. How we slept. Where we lived. Every technology we’ve ever brought inside the walls has quietly rewritten what it means to be human. Intelligence won’t be different. For ten thousand years, when you locked your door, you were the only intelligence inside. One day, the most unsettling thing about the past won’t be the lack of technology. It will be the realization that you could sit alone in a room, and nothing else in that room was thinking. And you never once appreciated the silence.
1:05

Jensen Huang just announced the death of the empty room. He listed it alongside dishwashers and lawn mowers. Like it was furniture. It’s not furniture. It’s the end of silence. We spent the last century buying machines to replace muscle. The lawnmower. The dishwasher. The engine. They were appliances. They saved us calories. Now we’re installing the machine that replaces agency. Huang: “It’s running all of your agents, it’s running all of your assistants, and they’re doing all kinds of things for you all the time.” Not when you ask. All the time. A PC waits for input. A smartphone waits for a tap. This doesn’t wait at all. It anticipates. It negotiates. It acts. It runs your life in the background while you sleep. Huang: “It becomes a lot more like R2-D2 to you. It becomes more like C-3PO to you, than it feels like a PC.” It doesn’t feel like a machine because it doesn’t act like one. It acts like a presence. Huang: “This reinvention of the computer is as big of a deal as the reinvention of the phone into what we now know as the smartphone.” He’s understating the math. The smartphone put a window to the world in your pocket. This puts a second mind in your living room. We didn’t just domesticate fire. Fire domesticated us. It changed what we ate. How we slept. Where we lived. Every technology we’ve ever brought inside the walls has quietly rewritten what it means to be human. Intelligence won’t be different. For ten thousand years, when you locked your door, you were the only intelligence inside. One day, the most unsettling thing about the past won’t be the lack of technology. It will be the realization that you could sit alone in a room, and nothing else in that room was thinking. And you never once appreciated the silence.

Dustin

19,306 Aufrufe • vor 1 Monat

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.
2:40

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