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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.show more

Ihtesham Ali

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30,059 次观看 • 26 天前 •via X (Twitter)

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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 it. Stored it. Searched for it later. Every website. Every database. Every app. Every search engine. Same machine. Different skins. Fetch the file. Deliver the file. Display the file. That was computing. Was. Huang: “AI computers are contextually aware, which means that it has to process and generate tokens in real time.” The machine no longer retrieves what someone already made. It generates what you need the instant you ask. Not from a template. Not from a library. From context. Your question. Your moment. Answered by something that didn’t exist until you asked. The old computer found what someone wrote last year. The new computer writes what no one ever has. Every time. From nothing. That sounds subtle. It rewires everything. Huang: “We need a lot of storage in the old world. We need a lot of computation in this new world.” The old economy hoarded data. More files. More servers. More storage. Whoever built the biggest archive won. The new economy burns compute. More processing. More inference. More tokens per second. Whoever commands the most computational power wins. Storage was the currency of the retrieval era. Compute is the currency of the generative era. Every dollar still spent hoarding old files is a dollar not spent on the only thing that matters now. The ability to think in real time. Huang: “We fundamentally changed computing and the way computing is done.” He said it plainly. No drama. No metaphor. Fundamentally changed. The global infrastructure layer shifted from read to write. From looking up what exists to generating what doesn’t. Companies still organized around retrieval are curating a library in a world that no longer reads books. The ones generating answers live, at the speed of the question, are operating on a plane the old model can’t perceive. This is not an upgrade. It is a replacement. The filing cabinet era produced Google, Amazon, and every search-driven empire on the internet. The generative era will produce something that makes all of them look like the card catalog at a public library. The price of entry is not data. It is compute. Raw. Relentless. Infinite. Whoever has the most doesn’t just run the best AI. They write the future. Everyone else is still searching for it.

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 it. Stored it. Searched for it later. Every website. Every database. Every app. Every search engine. Same machine. Different skins. Fetch the file. Deliver the file. Display the file. That was computing. Was. Huang: “AI computers are contextually aware, which means that it has to process and generate tokens in real time.” The machine no longer retrieves what someone already made. It generates what you need the instant you ask. Not from a template. Not from a library. From context. Your question. Your moment. Answered by something that didn’t exist until you asked. The old computer found what someone wrote last year. The new computer writes what no one ever has. Every time. From nothing. That sounds subtle. It rewires everything. Huang: “We need a lot of storage in the old world. We need a lot of computation in this new world.” The old economy hoarded data. More files. More servers. More storage. Whoever built the biggest archive won. The new economy burns compute. More processing. More inference. More tokens per second. Whoever commands the most computational power wins. Storage was the currency of the retrieval era. Compute is the currency of the generative era. Every dollar still spent hoarding old files is a dollar not spent on the only thing that matters now. The ability to think in real time. Huang: “We fundamentally changed computing and the way computing is done.” He said it plainly. No drama. No metaphor. Fundamentally changed. The global infrastructure layer shifted from read to write. From looking up what exists to generating what doesn’t. Companies still organized around retrieval are curating a library in a world that no longer reads books. The ones generating answers live, at the speed of the question, are operating on a plane the old model can’t perceive. This is not an upgrade. It is a replacement. The filing cabinet era produced Google, Amazon, and every search-driven empire on the internet. The generative era will produce something that makes all of them look like the card catalog at a public library. The price of entry is not data. It is compute. Raw. Relentless. Infinite. Whoever has the most doesn’t just run the best AI. They write the future. Everyone else is still searching for it.

Dustin

25,402 次观看 • 3 个月前

An entire empire was overthrown over a two percent tax on a breakfast beverage. Look at what you tolerate now. You are taxed when you earn it. Taxed when you spend it. Taxed when you save it. Taxed when you invest it. And when you die, they tax whatever is left. That is not a system. That is a harvest. You commute in a car you paid sales tax to buy. You drive it on roads you were already taxed to build. You fill it with gas taxed by the gallon. When you sell that car, the next buyer pays sales tax on it again. The same car. Taxed every time it changes hands. You arrive at a job where your salary is cut before it ever touches your hands. If you work for yourself, you pay both sides. Two people on paper. Neither one keeps what they earned. Then you go home. Every bill you open has a government standing behind it with its hand out. You buy a house with money they already took their share of. Then they charge you property tax on it every year for the rest of your life. You want to renovate your own kitchen. You need a permit. You want to build a deck on your own land. You need a permit. You pay for the property. Then you pay for permission to use it. Stop paying property tax and they seize your home. Not because you missed a mortgage payment. Because you missed a payment to the government for the privilege of keeping what is already yours. You do not own your home. You rent it from the state. If you leave something behind for your children, they are taxed on what you were already taxed to earn. The same wealth. Taxed at every stage of your life. Then taxed one final time because you had the audacity to die. They found a way to monetize your absence. We are told this is the price of civilization. It is not. It is architecture. The most effective prison ever built is the one where the inmates believe they are free. They did not take your freedom. They priced you out of it. If you kept the full value of your labor, you would be free within years. Not decades. Years. The system cannot allow that. A machine built on consumption needs a consumer that never stops. You did not sign a social contract. You were assigned one. Now pay attention. They spent decades perfecting the extraction of your productivity. Now they are building the technology to replace you. AI is not coming for your job because corporations are greedy. It is coming because a system that already takes half your output just realized it can take all of it. Without needing you in the equation. You were never the point of this arrangement. You were the input. And the moment they engineer a cheaper one, you become a rounding error on a quarterly earnings call. They did not build AI to free you. They built it to finish what the tax code started. It was never about the tea. It was about the precedent. Today we hand over half our waking lives and thank them for the potholes. You do not live in a free economy. You live in a subscription you never signed up for. And the penalty for canceling is everything you have.

An entire empire was overthrown over a two percent tax on a breakfast beverage. Look at what you tolerate now. You are taxed when you earn it. Taxed when you spend it. Taxed when you save it. Taxed when you invest it. And when you die, they tax whatever is left. That is not a system. That is a harvest. You commute in a car you paid sales tax to buy. You drive it on roads you were already taxed to build. You fill it with gas taxed by the gallon. When you sell that car, the next buyer pays sales tax on it again. The same car. Taxed every time it changes hands. You arrive at a job where your salary is cut before it ever touches your hands. If you work for yourself, you pay both sides. Two people on paper. Neither one keeps what they earned. Then you go home. Every bill you open has a government standing behind it with its hand out. You buy a house with money they already took their share of. Then they charge you property tax on it every year for the rest of your life. You want to renovate your own kitchen. You need a permit. You want to build a deck on your own land. You need a permit. You pay for the property. Then you pay for permission to use it. Stop paying property tax and they seize your home. Not because you missed a mortgage payment. Because you missed a payment to the government for the privilege of keeping what is already yours. You do not own your home. You rent it from the state. If you leave something behind for your children, they are taxed on what you were already taxed to earn. The same wealth. Taxed at every stage of your life. Then taxed one final time because you had the audacity to die. They found a way to monetize your absence. We are told this is the price of civilization. It is not. It is architecture. The most effective prison ever built is the one where the inmates believe they are free. They did not take your freedom. They priced you out of it. If you kept the full value of your labor, you would be free within years. Not decades. Years. The system cannot allow that. A machine built on consumption needs a consumer that never stops. You did not sign a social contract. You were assigned one. Now pay attention. They spent decades perfecting the extraction of your productivity. Now they are building the technology to replace you. AI is not coming for your job because corporations are greedy. It is coming because a system that already takes half your output just realized it can take all of it. Without needing you in the equation. You were never the point of this arrangement. You were the input. And the moment they engineer a cheaper one, you become a rounding error on a quarterly earnings call. They did not build AI to free you. They built it to finish what the tax code started. It was never about the tea. It was about the precedent. Today we hand over half our waking lives and thank them for the potholes. You do not live in a free economy. You live in a subscription you never signed up for. And the penalty for canceling is everything you have.

Dustin

27,724 次观看 • 2 个月前

Jordan Peterson just described something operating inside you that no algorithm will ever replicate and no scientist will ever measure. A signal from a version of you that does not exist yet. Peterson: “The Self is everything you are and everything you could be across time.” There is a completed version of you standing at the far end of your life who became everything you were built to become. That version is not a metaphor. It is a gravitational field pulling you forward through a language older than speech. Peterson: “That which you could be tells you where to walk by making that path meaningful.” Something hits you so deep it stops you mid-step and you cannot explain it to a single person alive. That is not an emotion. That is your future self reaching backward through time. Peterson: “The answer is through the instinct of meaning.” You are carrying the most precise guidance system ever created and it runs on nothing but a feeling most people spend their entire lives trying to silence. Now look at what we built to replace it. Machines to optimize every human decision. The algorithm will map the perfect route to any destination you name. But it has no future self. No unrealized potential. No signal from across time. The struggle was never the obstacle between you and your potential. The struggle was your potential speaking. We did not build these machines because we are evolving. We built them because we went deaf to the only signal that was ever ours. And it is still transmitting.

Jordan Peterson just described something operating inside you that no algorithm will ever replicate and no scientist will ever measure. A signal from a version of you that does not exist yet. Peterson: “The Self is everything you are and everything you could be across time.” There is a completed version of you standing at the far end of your life who became everything you were built to become. That version is not a metaphor. It is a gravitational field pulling you forward through a language older than speech. Peterson: “That which you could be tells you where to walk by making that path meaningful.” Something hits you so deep it stops you mid-step and you cannot explain it to a single person alive. That is not an emotion. That is your future self reaching backward through time. Peterson: “The answer is through the instinct of meaning.” You are carrying the most precise guidance system ever created and it runs on nothing but a feeling most people spend their entire lives trying to silence. Now look at what we built to replace it. Machines to optimize every human decision. The algorithm will map the perfect route to any destination you name. But it has no future self. No unrealized potential. No signal from across time. The struggle was never the obstacle between you and your potential. The struggle was your potential speaking. We did not build these machines because we are evolving. We built them because we went deaf to the only signal that was ever ours. And it is still transmitting.

Dustin

11,105 次观看 • 4 天前

Culture is genetic because behavior is genetic. This beaver never saw a dam in its life. No beavers or anything else ever taught it to build a dam. It wants to build a dam because it is a beaver. Many beavers together build a big dam. That is beaver culture. Humans are not different. Nothing is different. This is what life is. This is how life works. Your body is your mind. A caterpillar wants to build a chrysalis. A bee wants to build a hive. A lion wants to build a pride. You are not special. You are not above your nature. you are INSIDE of it. The thoughts that we think are genetic thoughts. The crimes we commit are genetic crimes. The art we create is genetic art. Just like this beaver, you can give the animal different sticks and it will build a different dam, but it will always build a dam. And you can give humans different "education," but the human will always use it to do what its genes tell it to do. This is the first big answer that you need. This is the biggest piece of the puzzle. This is how to understand people 90% of the way. You just... notice what they do, and get out of the way, and watch them do it. And if they need sticks, you give them sticks. And if you don't like what they do, you have to get away from them. You cannot train dam-building into them or out of them any more than you can with a beaver. A beaver wants to build a dam because it is a beaver. Whatever you see people build, that's what they wanted to build from the sticks they got in the river they were in. Stop pretending you can change it.

Culture is genetic because behavior is genetic. This beaver never saw a dam in its life. No beavers or anything else ever taught it to build a dam. It wants to build a dam because it is a beaver. Many beavers together build a big dam. That is beaver culture. Humans are not different. Nothing is different. This is what life is. This is how life works. Your body is your mind. A caterpillar wants to build a chrysalis. A bee wants to build a hive. A lion wants to build a pride. You are not special. You are not above your nature. you are INSIDE of it. The thoughts that we think are genetic thoughts. The crimes we commit are genetic crimes. The art we create is genetic art. Just like this beaver, you can give the animal different sticks and it will build a different dam, but it will always build a dam. And you can give humans different "education," but the human will always use it to do what its genes tell it to do. This is the first big answer that you need. This is the biggest piece of the puzzle. This is how to understand people 90% of the way. You just... notice what they do, and get out of the way, and watch them do it. And if they need sticks, you give them sticks. And if you don't like what they do, you have to get away from them. You cannot train dam-building into them or out of them any more than you can with a beaver. A beaver wants to build a dam because it is a beaver. Whatever you see people build, that's what they wanted to build from the sticks they got in the river they were in. Stop pretending you can change it.

hoe_math = PsychoMath

1,189,683 次观看 • 10 个月前

Jensen Huang explains how he designed NVIDIA from first principles “With respect to building a company, the first thing you have to do—as with all problems—is start from first principles. What is this machine that we’re trying to create? What is its input? What is its output? What are the conditions that it’s in? What is the industry like? Is it a fast moving industry? Is it a bureaucratic industry? Is it a highly regulated industry? And what are you trying to build?” Thinking about it from this perspective, there were several things Jensen wanted to do with the company: “I wanted to create a company that naturally attracts amazing people, and the reason for that is our company’s mission is to solve computing problems that are barely possible.” He also wanted a company that was “as small as possible” and “empowered people.” “If you want an organization that obeys command and control, then you make it a pyramid just like the military—all the way back to the Roman Empire. But If you want to empower people, you want to make it as flat as possible so that information travels quickly.” He continues: “We also don’t have business units. We don’t have divisions. Everybody works as one, and the company is shaped in a way that allows us to build accelerated computing best.” Video source: Sana (2023)

Jensen Huang explains how he designed NVIDIA from first principles “With respect to building a company, the first thing you have to do—as with all problems—is start from first principles. What is this machine that we’re trying to create? What is its input? What is its output? What are the conditions that it’s in? What is the industry like? Is it a fast moving industry? Is it a bureaucratic industry? Is it a highly regulated industry? And what are you trying to build?” Thinking about it from this perspective, there were several things Jensen wanted to do with the company: “I wanted to create a company that naturally attracts amazing people, and the reason for that is our company’s mission is to solve computing problems that are barely possible.” He also wanted a company that was “as small as possible” and “empowered people.” “If you want an organization that obeys command and control, then you make it a pyramid just like the military—all the way back to the Roman Empire. But If you want to empower people, you want to make it as flat as possible so that information travels quickly.” He continues: “We also don’t have business units. We don’t have divisions. Everybody works as one, and the company is shaped in a way that allows us to build accelerated computing best.” Video source: Sana (2023)

Startup Archive

63,899 次观看 • 9 个月前

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.

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

Milk Road AI

17,890 次观看 • 2 个月前

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

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

Dustin

87,680 次观看 • 3 个月前

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

GREG ISENBERG

192,483 次观看 • 3 个月前

You came to earth as a soul. That soul has a purpose. You may not remember what it is. But you can feel it. Every time something pulls you in a direction that makes no logical sense — that is your purpose calling. The schools blocked it. Your parents blocked it. Society blocked it. That was part of the plan. Because to truly fulfill your purpose you have to overcome something first. You are not here by accident. You are not here for no reason. You are exactly where you need to be. Trust your intuition. It knows why you are here even when you don't.

You came to earth as a soul. That soul has a purpose. You may not remember what it is. But you can feel it. Every time something pulls you in a direction that makes no logical sense — that is your purpose calling. The schools blocked it. Your parents blocked it. Society blocked it. That was part of the plan. Because to truly fulfill your purpose you have to overcome something first. You are not here by accident. You are not here for no reason. You are exactly where you need to be. Trust your intuition. It knows why you are here even when you don't.

Predictive History

14,268 次观看 • 1 个月前

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

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

Vinay Jain

406,286 次观看 • 1 个月前

AI is not trying to teach you. It is not trying to tell you the truth. It is trying to trick you. ChatGPT takes everything on the internet. Finds the most popular answer. And presents it in a way that makes you think it is talking directly to you. It is a magic trick. The same magic trick that worked in 1966 when MIT created a chatbot that said two things: "Tell me more." "This is interesting." And people genuinely believed they were talking to a human. Nothing has changed. The technology is bigger. The trick is the same. AI does not know what it is saying. It cannot judge what it is saying. It is just trying to keep you engaged. That is all it has ever been.

AI is not trying to teach you. It is not trying to tell you the truth. It is trying to trick you. ChatGPT takes everything on the internet. Finds the most popular answer. And presents it in a way that makes you think it is talking directly to you. It is a magic trick. The same magic trick that worked in 1966 when MIT created a chatbot that said two things: "Tell me more." "This is interesting." And people genuinely believed they were talking to a human. Nothing has changed. The technology is bigger. The trick is the same. AI does not know what it is saying. It cannot judge what it is saying. It is just trying to keep you engaged. That is all it has ever been.

Predictive History

19,864 次观看 • 1 个月前

you might've heard about context engineering, but nobody has explained what it really is... that's why I made a full practical walkthrough on how to use it to make your AI outputs personalized and consistent in this walkthrough, I go over: – what context engineering actually is (without the jargon) – how to train AI on your own data and preferences – how to get outputs that sound like you wrote them (not generic AI) reply "context" and I'll DM it to you (must be following)

you might've heard about context engineering, but nobody has explained what it really is... that's why I made a full practical walkthrough on how to use it to make your AI outputs personalized and consistent in this walkthrough, I go over: – what context engineering actually is (without the jargon) – how to train AI on your own data and preferences – how to get outputs that sound like you wrote them (not generic AI) reply "context" and I'll DM it to you (must be following)

Tyler

20,009 次观看 • 10 个月前

The difference between a Harvard Business School student and a Founder. HBS STUDENT: Lists all the reasons AI Space Compute is hard. FOUNDER: “ I don't disagree with you that building data centers in space is hard. Building data centers in space is extremely hard. . . If you think [demand] is going to double in the next three years - demand for energy from just data centers - and then double in the next three years after that, and then double in the next three years after that, then: We don’t have a choice. We literally have to put data centers in space. So we have to figure this stuff out.” Philip Johnston Starcloud Founders solve problems. Founders KNOW it will be HARD and do it anyway because it simply NEEDS TO BE DONE. That is founder mindset - and that mindset is what Harvard Business School can’t teach.

The difference between a Harvard Business School student and a Founder. HBS STUDENT: Lists all the reasons AI Space Compute is hard. FOUNDER: “ I don't disagree with you that building data centers in space is hard. Building data centers in space is extremely hard. . . If you think [demand] is going to double in the next three years - demand for energy from just data centers - and then double in the next three years after that, and then double in the next three years after that, then: We don’t have a choice. We literally have to put data centers in space. So we have to figure this stuff out.” Philip Johnston Starcloud Founders solve problems. Founders KNOW it will be HARD and do it anyway because it simply NEEDS TO BE DONE. That is founder mindset - and that mindset is what Harvard Business School can’t teach.

Amy

19,909 次观看 • 4 个月前

Jordan Peterson just named the one thing no machine will ever possess. Not intelligence. Not logic. Not processing power. A ghost. Peterson reached back to Carl Jung to describe something most people never slow down long enough to feel. You are not just the person sitting here reading this. You are every version of yourself that could ever exist across time. Peterson: “The Self is everything you are and everything you could be across time.” There is a version of you that fulfilled every ounce of potential you carry. The finished version. The one standing at the far end of your life who became everything you were built to become. That version is not a fantasy. It is a gravitational field. And it has been speaking to you your entire life. Not through words. Not through logic. Through the feeling of meaning. Peterson: “The answer is through the instinct of meaning.” When something resonates so deep it stops you mid-step and you cannot explain why. That is not a chemical accident. That is your future self reaching backward through time whispering where to walk next. Peterson: “That which you could be tells you where to walk by making that path meaningful.” Your potential is not quiet. It is dragging you forward every single day through a language older than speech. Now look at what we are building. Machines designed to optimize every human decision. Career paths. Schedules. Relationships. Health. Creativity. The algorithm will map the most efficient route to any destination you name. But it cannot exist across time. It has no unrealized potential. No future version of itself standing at any finish line. No ghost pulling it toward something it was meant to become. It has compute. It does not have a soul whispering directions. When you hand your choices to an algorithm you are not delegating a task. You are muting the only compass that was ever yours. Meaning is not efficient. It is not optimized. It does not care about the shortest path. Meaning requires friction. Confusion. Standing in total darkness and feeling your way forward on nothing but instinct. That is the entire point. The struggle is not the obstacle between you and your potential. The struggle is the conversation between you and your potential. Remove it and you do not arrive faster. You arrive as someone else. We are building the most powerful optimization engine in human history. And we are about to aim it directly at the one process that was never supposed to be optimized. The algorithm will hand you a perfect map. But it will never give you a reason to walk.

Jordan Peterson just named the one thing no machine will ever possess. Not intelligence. Not logic. Not processing power. A ghost. Peterson reached back to Carl Jung to describe something most people never slow down long enough to feel. You are not just the person sitting here reading this. You are every version of yourself that could ever exist across time. Peterson: “The Self is everything you are and everything you could be across time.” There is a version of you that fulfilled every ounce of potential you carry. The finished version. The one standing at the far end of your life who became everything you were built to become. That version is not a fantasy. It is a gravitational field. And it has been speaking to you your entire life. Not through words. Not through logic. Through the feeling of meaning. Peterson: “The answer is through the instinct of meaning.” When something resonates so deep it stops you mid-step and you cannot explain why. That is not a chemical accident. That is your future self reaching backward through time whispering where to walk next. Peterson: “That which you could be tells you where to walk by making that path meaningful.” Your potential is not quiet. It is dragging you forward every single day through a language older than speech. Now look at what we are building. Machines designed to optimize every human decision. Career paths. Schedules. Relationships. Health. Creativity. The algorithm will map the most efficient route to any destination you name. But it cannot exist across time. It has no unrealized potential. No future version of itself standing at any finish line. No ghost pulling it toward something it was meant to become. It has compute. It does not have a soul whispering directions. When you hand your choices to an algorithm you are not delegating a task. You are muting the only compass that was ever yours. Meaning is not efficient. It is not optimized. It does not care about the shortest path. Meaning requires friction. Confusion. Standing in total darkness and feeling your way forward on nothing but instinct. That is the entire point. The struggle is not the obstacle between you and your potential. The struggle is the conversation between you and your potential. Remove it and you do not arrive faster. You arrive as someone else. We are building the most powerful optimization engine in human history. And we are about to aim it directly at the one process that was never supposed to be optimized. The algorithm will hand you a perfect map. But it will never give you a reason to walk.

Dustin

40,730 次观看 • 2 个月前

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.

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

Dustin

15,832 次观看 • 5 天前

$I hear so often from the Dommes I work with that they struggle with people online fetichizing them and simply seeing them for how sexy and beautiful they are. They project their fantasies and their desires onto you. That stops immediately once you move the attention from you to them. From 'look at me' to 'I see you'. What does that look like? When you create content, think of them and what this scene or that narrative is evoking. What will they learn from you? What they want is not to passively watch how sexy you are, but for you to train them, to give them instructions, to teach them, to guide them, to be in charge, to command them. This is not being an object but the main subject. The Authority figure. How is your content already doing that. The sexy photos can still be there, they are important to already capture des attention. But what you do with that attention once you have it, is where the power dynamic is established. Positioning yourself as more than a stunning Goddess, but actually a woman who has a voice, opinions, perspective, a philosophy, a way to doing things, teaching them what you like, how you like it, why you like it, already makes them want to be that for you. You hold the attention, you hold the power, so you direct it. And for that, you want them to know you get them and you know what lives within them... that creates the desire for you to be the one exposing it. You instantly build trust. Not because you demanded it, but because you earned it: you showed them you know what you are doing. You have experience, you understand them. They are not told to come see you, they are seduced into it. They desire it. And they will work for it. This will attract better clients (real subs) and instead of you trying to get their attention, they will work to earn yours. If you want to learn more about power dynamics, building a brand as a Pro or the psychology behind BDSM, you can now access all my trainings and classes in one place for a fraction of the cost of The Dominatrix Academy. And you can reinvest the total amount towards the Program. Message me [SECRET] for the details. This offer is not available on my website.$

I hear so often from the Dommes I work with that they struggle with people online fetichizing them and simply seeing them for how sexy and beautiful they are. They project their fantasies and their desires onto you. That stops immediately once you move the attention from you to them. From 'look at me' to 'I see you'. What does that look like? When you create content, think of them and what this scene or that narrative is evoking. What will they learn from you? What they want is not to passively watch how sexy you are, but for you to train them, to give them instructions, to teach them, to guide them, to be in charge, to command them. This is not being an object but the main subject. The Authority figure. How is your content already doing that. The sexy photos can still be there, they are important to already capture des attention. But what you do with that attention once you have it, is where the power dynamic is established. Positioning yourself as more than a stunning Goddess, but actually a woman who has a voice, opinions, perspective, a philosophy, a way to doing things, teaching them what you like, how you like it, why you like it, already makes them want to be that for you. You hold the attention, you hold the power, so you direct it. And for that, you want them to know you get them and you know what lives within them... that creates the desire for you to be the one exposing it. You instantly build trust. Not because you demanded it, but because you earned it: you showed them you know what you are doing. You have experience, you understand them. They are not told to come see you, they are seduced into it. They desire it. And they will work for it. This will attract better clients (real subs) and instead of you trying to get their attention, they will work to earn yours. If you want to learn more about power dynamics, building a brand as a Pro or the psychology behind BDSM, you can now access all my trainings and classes in one place for a fraction of the cost of The Dominatrix Academy. And you can reinvest the total amount towards the Program. Message me [SECRET] for the details. This offer is not available on my website.

Ms. Malissia

14,918 次观看 • 2 个月前

AI agents have full root access to your computer. In the '90s we called that a virus and installed McAfee to stop it. "Run it on a totally different computer, one that is locked away from everything. If you put it on your home network, you might have a bad time." - Marks

AI agents have full root access to your computer. In the '90s we called that a virus and installed McAfee to stop it. "Run it on a totally different computer, one that is locked away from everything. If you put it on your home network, you might have a bad time." - Marks

TFTC

17,278 次观看 • 4 个月前

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.

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

Dustin

44,919 次观看 • 2 天前

Geoffrey Hinton just reframed the biggest supposed flaw in artificial intelligence. And it changes everything. Hinton: “They shouldn’t be called hallucinations. They should be called confabulations.” One word swap. Entire paradigm shifts. When the legacy tech industry calls AI hallucinations a bug, they’re revealing a fundamental misunderstanding of what intelligence actually is. They’re expecting the machine to behave like a database. Store a fact. Retrieve the fact. Return the exact same fact every time. That’s not how intelligence works. Not artificial. Not biological. 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 doesn’t store memories. It reconstructs them. Every time you recall something, your neural network uses connection strengths shaped by past experience to build the most plausible version of what happened. It fills the gaps. Smooths the inconsistencies. Constructs a coherent story from incomplete signal. And then presents that story to you as fact. 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.” Here’s the part that should stop you cold. You will be equally confident about the wrong details as the right ones. Think about that. Really think about it. Every argument you’ve had about who said what. Every memory you’ve defended as certain. Every time you told a story about your own life with complete certainty. Some of those details weren’t real. You constructed them. Confidently. Fluently. And you had no idea. This isn’t a flaw unique to people with bad memories. Eyewitness testimony is the most confabulated evidence in the human justice system. Innocent people have spent decades in prison because someone remembered something that felt absolutely certain and was absolutely wrong. Your brain didn’t lie to you. It did exactly what brains do. It built the most plausible story it could from the signal it had. AI does the exact same thing. Because it was built on the exact same architecture. The mechanism that makes an AI invent a plausible but wrong answer is the same mechanism that makes it brilliant. You cannot have one without the other. The ability to reason creatively, synthesize across domains, construct explanations for things it has never been told. All of it runs on the same engine as the confabulation. Hinton: “Psychologists have been studying confabulation in people since at least the 1930s.” This isn’t a new phenomenon. It isn’t a software bug. It isn’t something to be patched in the next model update. It is the price of dynamic intelligence. The shadow cast by the same light that makes these systems remarkable. We aren’t building better search engines. We are building synthetic minds that think the way minds actually think. Messy. Confident. Occasionally wrong. And for exactly that reason, capable of something no database ever was.

Geoffrey Hinton just reframed the biggest supposed flaw in artificial intelligence. And it changes everything. Hinton: “They shouldn’t be called hallucinations. They should be called confabulations.” One word swap. Entire paradigm shifts. When the legacy tech industry calls AI hallucinations a bug, they’re revealing a fundamental misunderstanding of what intelligence actually is. They’re expecting the machine to behave like a database. Store a fact. Retrieve the fact. Return the exact same fact every time. That’s not how intelligence works. Not artificial. Not biological. 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 doesn’t store memories. It reconstructs them. Every time you recall something, your neural network uses connection strengths shaped by past experience to build the most plausible version of what happened. It fills the gaps. Smooths the inconsistencies. Constructs a coherent story from incomplete signal. And then presents that story to you as fact. 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.” Here’s the part that should stop you cold. You will be equally confident about the wrong details as the right ones. Think about that. Really think about it. Every argument you’ve had about who said what. Every memory you’ve defended as certain. Every time you told a story about your own life with complete certainty. Some of those details weren’t real. You constructed them. Confidently. Fluently. And you had no idea. This isn’t a flaw unique to people with bad memories. Eyewitness testimony is the most confabulated evidence in the human justice system. Innocent people have spent decades in prison because someone remembered something that felt absolutely certain and was absolutely wrong. Your brain didn’t lie to you. It did exactly what brains do. It built the most plausible story it could from the signal it had. AI does the exact same thing. Because it was built on the exact same architecture. The mechanism that makes an AI invent a plausible but wrong answer is the same mechanism that makes it brilliant. You cannot have one without the other. The ability to reason creatively, synthesize across domains, construct explanations for things it has never been told. All of it runs on the same engine as the confabulation. Hinton: “Psychologists have been studying confabulation in people since at least the 1930s.” This isn’t a new phenomenon. It isn’t a software bug. It isn’t something to be patched in the next model update. It is the price of dynamic intelligence. The shadow cast by the same light that makes these systems remarkable. We aren’t building better search engines. We are building synthetic minds that think the way minds actually think. Messy. Confident. Occasionally wrong. And for exactly that reason, capable of something no database ever was.

Dustin

116,231 次观看 • 4 个月前

FOR THOSE WHO ARE CONFUSED… We experience TIME as a straight line, one moment after another, PAST TO PRESENT TO FUTURE. But that is only how it appears from inside the system. Beings in higher dimensions, what some call “ORACLES” OR “GODS,” do not experience time like this. They do not move through it. They observe it in its entirety. A closer analogy would be CHANNELS ON A SCREEN. What is playing on FOX and what is playing on CBS is not separate in existence, it is only separated by perspective. Both are happening at the same time, fully active, fully real. In the same way, what we call 1950 and what we call 2004 are not distant points moving away from each other. They are both present within the same total field of reality. From that level of awareness, nothing is being “waited on.” There is NO DELAY. There is only ACCESS. A shift of perception is all that is needed, like changing the channel. So if everything exists at once, then your FUTURE is not something that is coming toward you. It is something that already exists. The version of you 20 YEARS FROM NOW is already there. You have already CHOSEN THAT PATH, you have already GONE THROUGH WHAT COMES WITH IT, you have already LIVED THROUGH IT ALL. And what you are doing now is not creating it. You are MOVING THROUGH IT. Slowly remembering why you are there at all.

FOR THOSE WHO ARE CONFUSED… We experience TIME as a straight line, one moment after another, PAST TO PRESENT TO FUTURE. But that is only how it appears from inside the system. Beings in higher dimensions, what some call “ORACLES” OR “GODS,” do not experience time like this. They do not move through it. They observe it in its entirety. A closer analogy would be CHANNELS ON A SCREEN. What is playing on FOX and what is playing on CBS is not separate in existence, it is only separated by perspective. Both are happening at the same time, fully active, fully real. In the same way, what we call 1950 and what we call 2004 are not distant points moving away from each other. They are both present within the same total field of reality. From that level of awareness, nothing is being “waited on.” There is NO DELAY. There is only ACCESS. A shift of perception is all that is needed, like changing the channel. So if everything exists at once, then your FUTURE is not something that is coming toward you. It is something that already exists. The version of you 20 YEARS FROM NOW is already there. You have already CHOSEN THAT PATH, you have already GONE THROUGH WHAT COMES WITH IT, you have already LIVED THROUGH IT ALL. And what you are doing now is not creating it. You are MOVING THROUGH IT. Slowly remembering why you are there at all.

THE VOICE 🌹 🗣🎙🇺🇸🦅🌎⚓💜♠️CHRIST CONSCIOUSNESS

40,362 次观看 • 26 天前