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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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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 2 Monaten

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

55,974 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

17,911 Aufrufe • vor 3 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

43,505 Aufrufe • vor 5 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

42,960 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

57,215 Aufrufe • vor 4 Monaten

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

14,565 Aufrufe • vor 5 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

105,201 Aufrufe • vor 4 Monaten

Elon Musk was asked how fast AI is moving, and answered by correcting the most aggressive forecaster in technology for not being aggressive enough. Musk: “I have to give credit to Ray Kurzweil in being actually remarkably accurate in his predictions. If anything, I think he was perhaps a bit conservative in his predictions.” Kurzweil spent thirty years publishing timelines that were treated as proof he had lost the plot. He hit nearly all of them. The word Musk used for that record was conservative. Kurzweil built his forecasts by reading the rate of change. Musk is reading it now. Musk: “The dedicated AI compute appears to be growing by a factor of 10 every six months.” That is not a projection. “Appears to be growing” describes something that has already happened. Musk: “Almost a 100x improvement per year, at least for the next few years.” Moore’s Law was 2x every two years. That one curve produced the internet, the smartphone, the cloud, and every instinct you have about how fast the world can change. Your sense of normal was calibrated on 2x. The system is running at 100x. The new world is not being built next to the old one. Musk: “Probably a lot of the data centers, maybe most of the data centers that currently do conventional compute, will transition to AI compute.” The infrastructure holding up the current economy is being converted into what replaces it. The old world is the raw material for the next one. Every generation assumes the speed it grew up with is the speed of history. Ours is the first to be handed the actual number and still round it down. Everything you build takes time. A child, a trade, a life’s work. All of it rests on the assumption that the world will still be recognizable when the work is finished. That assumption has held for every human who has ever lived. It was never a law of nature. It was a side effect of how slowly things moved. The most extreme forecast on record came in low. Reasonable is no longer the safe position. It is only the comfortable one.
1:01

Elon Musk was asked how fast AI is moving, and answered by correcting the most aggressive forecaster in technology for not being aggressive enough. Musk: “I have to give credit to Ray Kurzweil in being actually remarkably accurate in his predictions. If anything, I think he was perhaps a bit conservative in his predictions.” Kurzweil spent thirty years publishing timelines that were treated as proof he had lost the plot. He hit nearly all of them. The word Musk used for that record was conservative. Kurzweil built his forecasts by reading the rate of change. Musk is reading it now. Musk: “The dedicated AI compute appears to be growing by a factor of 10 every six months.” That is not a projection. “Appears to be growing” describes something that has already happened. Musk: “Almost a 100x improvement per year, at least for the next few years.” Moore’s Law was 2x every two years. That one curve produced the internet, the smartphone, the cloud, and every instinct you have about how fast the world can change. Your sense of normal was calibrated on 2x. The system is running at 100x. The new world is not being built next to the old one. Musk: “Probably a lot of the data centers, maybe most of the data centers that currently do conventional compute, will transition to AI compute.” The infrastructure holding up the current economy is being converted into what replaces it. The old world is the raw material for the next one. Every generation assumes the speed it grew up with is the speed of history. Ours is the first to be handed the actual number and still round it down. Everything you build takes time. A child, a trade, a life’s work. All of it rests on the assumption that the world will still be recognizable when the work is finished. That assumption has held for every human who has ever lived. It was never a law of nature. It was a side effect of how slowly things moved. The most extreme forecast on record came in low. Reasonable is no longer the safe position. It is only the comfortable one.

Dustin

171,981 Aufrufe • vor 23 Tagen

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

92,704 Aufrufe • vor 3 Monaten

Jensen Huang told a room of graduates that nobody has a head start on them. He wasn’t being nice. Huang: “This is the best of times to be in school. This is the best of times to be graduating from school, because the world is reset.” Reset is an engineering word, not a motivational one. It means accumulated state is cleared. The machine restarts from a known position. He chose it on purpose. Huang: “An entire industry, the largest industry in the world, the computer industry, is reset. And because every industry in the world is built onto the computer industry, every industry is reset.” Logistics. Insurance. Farming. Film. All of it runs on computation, which means none of it gets to opt out. When the layer underneath moves, everything standing on it moves. Noticing is optional. Huang: “You are at exactly the same place as everybody else. Nobody has a head start on you.” Somewhere, a fifty-year-old heard the same sentence and did not feel encouraged. Identical fact. Different chair. A reset doesn’t delete what anyone knows. It deletes the premium on having known it first. The knowledge keeps its value. It stops paying interest. Seniority was always a bet that the ground holds still. Every generation before this one had elders to ask. On this, the most experienced person alive has about three years on you. Expertise here can’t be inherited. It gets built, and whoever builds it first becomes the person everyone else asks. Huang: “This is the perfect time to engage the most powerful technology the world’s ever known. It is personalized. Everybody has it on their browser. It is accessible. Obviously everybody’s using it.” Notice what he isn’t describing. No capital requirement. No license. No lab. Every general-purpose technology before this one gated on money or access. Steam needed a factory. Electricity needed a grid. Semiconductors need a fab. This one needs an open tab. The constraint moved somewhere uncomfortable. It used to be access. Now it’s whether you bother. Huang: “And put it to use in service of your career, in service of your dreams, to solve great problems. I can’t imagine how excited you must be, and yet I hear sometimes you’re concerned about the future.” The excited ones and the frightened ones are reading identical information. They differ only in what they do next. Fear is the correct measurement of a reset. It isn’t the correct conclusion. Huang: “I just need you to know that what I see on the other side is a welcoming industry looking for new college grads who are expert at using AI. Whether it’s expert at using AI for marketing or finance or engineering or software engineering, we are looking for expert AI users.” Read the criterion. Not a school. Not a transcript. Not years served. The qualification is a verb, and nobody holds a decade of it. Every advantage anyone has ever held began in a year when nobody had one. Every fortune, every dynasty, every edge you have ever resented traces back to a window like this one, and to the few who moved inside it. Resets expire. Nobody has a head start on you. That is true today. It gets less true every quarter, and by year’s end it will be somebody’s head start. Probably somebody who heard the same sentence you did. Waiting doesn’t feel like a decision. That’s what makes it the most common one. Everyone who ever missed one of these was busy, reasonable, and right about everything except the timing. A level field is not a gift. It’s a countdown.
1:19

Jensen Huang told a room of graduates that nobody has a head start on them. He wasn’t being nice. Huang: “This is the best of times to be in school. This is the best of times to be graduating from school, because the world is reset.” Reset is an engineering word, not a motivational one. It means accumulated state is cleared. The machine restarts from a known position. He chose it on purpose. Huang: “An entire industry, the largest industry in the world, the computer industry, is reset. And because every industry in the world is built onto the computer industry, every industry is reset.” Logistics. Insurance. Farming. Film. All of it runs on computation, which means none of it gets to opt out. When the layer underneath moves, everything standing on it moves. Noticing is optional. Huang: “You are at exactly the same place as everybody else. Nobody has a head start on you.” Somewhere, a fifty-year-old heard the same sentence and did not feel encouraged. Identical fact. Different chair. A reset doesn’t delete what anyone knows. It deletes the premium on having known it first. The knowledge keeps its value. It stops paying interest. Seniority was always a bet that the ground holds still. Every generation before this one had elders to ask. On this, the most experienced person alive has about three years on you. Expertise here can’t be inherited. It gets built, and whoever builds it first becomes the person everyone else asks. Huang: “This is the perfect time to engage the most powerful technology the world’s ever known. It is personalized. Everybody has it on their browser. It is accessible. Obviously everybody’s using it.” Notice what he isn’t describing. No capital requirement. No license. No lab. Every general-purpose technology before this one gated on money or access. Steam needed a factory. Electricity needed a grid. Semiconductors need a fab. This one needs an open tab. The constraint moved somewhere uncomfortable. It used to be access. Now it’s whether you bother. Huang: “And put it to use in service of your career, in service of your dreams, to solve great problems. I can’t imagine how excited you must be, and yet I hear sometimes you’re concerned about the future.” The excited ones and the frightened ones are reading identical information. They differ only in what they do next. Fear is the correct measurement of a reset. It isn’t the correct conclusion. Huang: “I just need you to know that what I see on the other side is a welcoming industry looking for new college grads who are expert at using AI. Whether it’s expert at using AI for marketing or finance or engineering or software engineering, we are looking for expert AI users.” Read the criterion. Not a school. Not a transcript. Not years served. The qualification is a verb, and nobody holds a decade of it. Every advantage anyone has ever held began in a year when nobody had one. Every fortune, every dynasty, every edge you have ever resented traces back to a window like this one, and to the few who moved inside it. Resets expire. Nobody has a head start on you. That is true today. It gets less true every quarter, and by year’s end it will be somebody’s head start. Probably somebody who heard the same sentence you did. Waiting doesn’t feel like a decision. That’s what makes it the most common one. Everyone who ever missed one of these was busy, reasonable, and right about everything except the timing. A level field is not a gift. It’s a countdown.

Dustin

19,113 Aufrufe • vor 29 Tagen

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

282,792 Aufrufe • vor 5 Monaten

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

185,568 Aufrufe • vor 7 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

19,801 Aufrufe • vor 2 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

57,595 Aufrufe • vor 4 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

50,551 Aufrufe • vor 1 Monat

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

16,260 Aufrufe • vor 1 Monat

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

554,328 Aufrufe • vor 5 Monaten

Yann LeCun just told the most well-funded industry in human history it is solving the wrong problem. LeCun: “Babies learn this around the age of eight or nine months, that objects don’t float, they fall.” No dataset. No labels. No reward signal. A nine month old drops a spoon and builds a physics engine no machine can match. LeCun: “Most of us can learn to drive in about 20 or 30 hours of training without ever crashing, causing any accident.” Twenty hours. Tesla has built the most capable driving system on the road. It took billions of miles of data to get there. A sixteen year old gets there over a long weekend. Not because the teenager is the better driver. Because the teenager is not learning to drive. They are deploying a model of reality they have been building since birth. LeCun: “If we drive next to a cliff, we know that if we turn the wheel to the right, the car is going to run off the cliff and nothing good is going to come out of this.” You simulate the crash. You see the wreckage. You feel the fall. You turn the wheel. None of it was real. All of it was intelligence. Every AI has to crash a thousand times to learn what you imagined once and never did. That is not a performance gap. That is an architecture gap. LeCun: “The main problem we need to solve is how do we learn models of the world.” Not bigger models. Not more compute. Not another trillion tokens. World models. A machine that can run reality forward before it acts. The industry is scaling language. LeCun says language is a compression of thought. Not thought itself. You understood gravity before you could say the word. You grasped cause and effect before your first sentence. The deepest intelligence you will ever possess was built in total silence. And every lab on Earth is trying to reconstruct the mind from words alone. Physics does not care about your context window. A baby who learns that cups fall in a kitchen already knows that rocks fall off cliffs. No retraining. No fine-tuning. One model. Every environment. That is what intelligence actually is. Not prediction. Not pattern matching. Not scale. A simulation of reality so precise you rehearse the future before it exists. Every infant on Earth builds one. No machine ever has.
1:45

Yann LeCun just told the most well-funded industry in human history it is solving the wrong problem. LeCun: “Babies learn this around the age of eight or nine months, that objects don’t float, they fall.” No dataset. No labels. No reward signal. A nine month old drops a spoon and builds a physics engine no machine can match. LeCun: “Most of us can learn to drive in about 20 or 30 hours of training without ever crashing, causing any accident.” Twenty hours. Tesla has built the most capable driving system on the road. It took billions of miles of data to get there. A sixteen year old gets there over a long weekend. Not because the teenager is the better driver. Because the teenager is not learning to drive. They are deploying a model of reality they have been building since birth. LeCun: “If we drive next to a cliff, we know that if we turn the wheel to the right, the car is going to run off the cliff and nothing good is going to come out of this.” You simulate the crash. You see the wreckage. You feel the fall. You turn the wheel. None of it was real. All of it was intelligence. Every AI has to crash a thousand times to learn what you imagined once and never did. That is not a performance gap. That is an architecture gap. LeCun: “The main problem we need to solve is how do we learn models of the world.” Not bigger models. Not more compute. Not another trillion tokens. World models. A machine that can run reality forward before it acts. The industry is scaling language. LeCun says language is a compression of thought. Not thought itself. You understood gravity before you could say the word. You grasped cause and effect before your first sentence. The deepest intelligence you will ever possess was built in total silence. And every lab on Earth is trying to reconstruct the mind from words alone. Physics does not care about your context window. A baby who learns that cups fall in a kitchen already knows that rocks fall off cliffs. No retraining. No fine-tuning. One model. Every environment. That is what intelligence actually is. Not prediction. Not pattern matching. Not scale. A simulation of reality so precise you rehearse the future before it exists. Every infant on Earth builds one. No machine ever has.

Dustin

122,066 Aufrufe • vor 1 Monat

Jensen Huang was asked about the people technology left behind. He didn't offer a plan. He said the gap already closed. Huang: "All of a sudden artificial intelligence closed that technology divide." That divide was never a gap in ability. It was a language requirement. Huang: "Anybody could be a software programmer now." Every tool we ever built charged admission, and the price was always a language. The press needed literacy. The engine needed the manual. The computer needed code. Every tool in history had the same shape. The human moved toward the machine, compressed into a form it could parse. Whoever couldn't compress stayed outside. Code was always a human speaking machine. Seventy years of people translating themselves down into something a processor would accept. It just learned to speak back. Nothing has ever moved in that direction before. So we sorted people by the toll and pretended we were sorting by mind. The ones who paid became skilled. Everyone else became unskilled, a word that has never once described a real person. It only meant fluent in nothing the market was buying. Huang: "Everybody who are really gifted at their craft but maybe they don't know how to scale themselves with technology, they now have AI to help scale them." The best cook in a village of four thousand died the best cook in a village of four thousand. Not from a shortage of ability, but from a second requirement that had nothing to do with the first. Go back far enough in your own family and there is someone who was extraordinary at something. The world never found out. Neither did they. Ability was never distributed by geography. Access was, and access is the only thing that got recorded. Every system you move through in a day was built by the narrow band who could speak to a machine. Not the best ideas anyone had. The ideas that survived translation. We have never once seen what the rest of the species would have made. The scarcity was never in the talent. It was in the distance between holding it and reaching anyone. That distance was the product the technology industry sold. Huang: "They're welcomed into the world's economy, not burdened by technology anymore because AI made that possible." Burdened. Technology sold itself as leverage for a century, and the man supplying the whole industry just called it a weight. A developer you couldn't afford. A site that broke on a Sunday with no one to call. You paid the technology industry for permission to be findable. Nobody on earth got smarter this decade. The door stopped asking for a password. Huang: "Five years from now, it is likely that we're all going to be more gainfully employed. The economy is gonna be more productive." He grounds that in the labor shortage already on the books. Open work with nobody there to do it, inside an economy panicking about a machine that takes work away. Both cannot be true. The fear says there won't be enough work for us. The ledger says there aren't enough of us for the work. Every time a tool stopped requiring a specialist, the specialist lost a monopoly and everyone else gained a century. Writing left the scribes. The press left the church. The computer left the lab. The barrier was also a shelter. Everyone left outside got to keep the version of themselves that was never tested. For most of history that was a mercy. The wall did the refusing, so you never had to hear it from anyone else. The wall is gone. Now you find out. Nothing about you changed. The requirement did. For the first time, the only thing between what you can do and who it reaches is whether you do it.
1:44

Jensen Huang was asked about the people technology left behind. He didn't offer a plan. He said the gap already closed. Huang: "All of a sudden artificial intelligence closed that technology divide." That divide was never a gap in ability. It was a language requirement. Huang: "Anybody could be a software programmer now." Every tool we ever built charged admission, and the price was always a language. The press needed literacy. The engine needed the manual. The computer needed code. Every tool in history had the same shape. The human moved toward the machine, compressed into a form it could parse. Whoever couldn't compress stayed outside. Code was always a human speaking machine. Seventy years of people translating themselves down into something a processor would accept. It just learned to speak back. Nothing has ever moved in that direction before. So we sorted people by the toll and pretended we were sorting by mind. The ones who paid became skilled. Everyone else became unskilled, a word that has never once described a real person. It only meant fluent in nothing the market was buying. Huang: "Everybody who are really gifted at their craft but maybe they don't know how to scale themselves with technology, they now have AI to help scale them." The best cook in a village of four thousand died the best cook in a village of four thousand. Not from a shortage of ability, but from a second requirement that had nothing to do with the first. Go back far enough in your own family and there is someone who was extraordinary at something. The world never found out. Neither did they. Ability was never distributed by geography. Access was, and access is the only thing that got recorded. Every system you move through in a day was built by the narrow band who could speak to a machine. Not the best ideas anyone had. The ideas that survived translation. We have never once seen what the rest of the species would have made. The scarcity was never in the talent. It was in the distance between holding it and reaching anyone. That distance was the product the technology industry sold. Huang: "They're welcomed into the world's economy, not burdened by technology anymore because AI made that possible." Burdened. Technology sold itself as leverage for a century, and the man supplying the whole industry just called it a weight. A developer you couldn't afford. A site that broke on a Sunday with no one to call. You paid the technology industry for permission to be findable. Nobody on earth got smarter this decade. The door stopped asking for a password. Huang: "Five years from now, it is likely that we're all going to be more gainfully employed. The economy is gonna be more productive." He grounds that in the labor shortage already on the books. Open work with nobody there to do it, inside an economy panicking about a machine that takes work away. Both cannot be true. The fear says there won't be enough work for us. The ledger says there aren't enough of us for the work. Every time a tool stopped requiring a specialist, the specialist lost a monopoly and everyone else gained a century. Writing left the scribes. The press left the church. The computer left the lab. The barrier was also a shelter. Everyone left outside got to keep the version of themselves that was never tested. For most of history that was a mercy. The wall did the refusing, so you never had to hear it from anyone else. The wall is gone. Now you find out. Nothing about you changed. The requirement did. For the first time, the only thing between what you can do and who it reaches is whether you do it.

Dustin

431,058 Aufrufe • vor 1 Monat