Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

A robot just worked an 8-hour shift in China. Then it handled an error no human flagged, adapting to a conveyor that shifted under it and correcting the position deviation on its own before carrying on. This is AgiBot's G2 at Longcheer in Nanchang, where the fleet has now...

heyshrutimishra's profile picture

Shruti

182,075 subscribers

11,014 görüntüleme • 2 ay önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Figure 03 just finished an 8-hour work livestream, imperfect, but already good enough to replace a lot of repetitive warehouse labor. 🤖 Brett Adcock put a team of F.03 robots on a factory-style package sorting task for a full shift. The job was simple and brutal: detect the barcode, pick the package, flip it label-side down, place it on the conveyor, repeat. Soft poly bags, rigid boxes, moving belts, messy orientations. That is exactly the kind of boring physical work factories pay humans to do all day. Early in the stream, the system handled 230 packages in 10 minutes. That is roughly 2.6 seconds per item — already in human-speed territory for this narrow workflow. The more important part: it was not one robot pretending to work all day. It was a team of Figure 03 robots keeping the line running. When one robot ran low on battery, it left the station and another robot stepped in. That is the real factory signal: not just autonomy, but shift continuity. F.03 is rated for about 5 hours of runtime, so the 8-hour result depends on fleet orchestration, charging, and handoff. That matters more than a single clean demo. The stream was not perfect. There were pauses, hesitations, missed orientations, and small recovery moments. Good. A perfect short clip hides failure. An 8-hour livestream exposes the parts that actually matter: endurance, recovery, throughput, and whether the robot can stay useful after the novelty wears off. Figure says this was fully autonomous on Helix-02, with zero human intervention. For logistics and manufacturing, that is the threshold worth watching. Not “can it do one impressive task?” Can it keep doing the boring task for an entire shift? Figure is not showing a general human replacement yet. But for structured, repetitive factory work, the gap just got much smaller. The timing is also interesting: Figure says BotQ has already delivered 350+ F.03 units and reached a 1 robot/hour production cadence. And F.04 is now in full design lock, with parts starting to ship. The next test is obvious. 8 hours was the proof of endurance. 24/7 is the proof of labor economics.
0:25

Figure 03 just finished an 8-hour work livestream, imperfect, but already good enough to replace a lot of repetitive warehouse labor. 🤖 Brett Adcock put a team of F.03 robots on a factory-style package sorting task for a full shift. The job was simple and brutal: detect the barcode, pick the package, flip it label-side down, place it on the conveyor, repeat. Soft poly bags, rigid boxes, moving belts, messy orientations. That is exactly the kind of boring physical work factories pay humans to do all day. Early in the stream, the system handled 230 packages in 10 minutes. That is roughly 2.6 seconds per item — already in human-speed territory for this narrow workflow. The more important part: it was not one robot pretending to work all day. It was a team of Figure 03 robots keeping the line running. When one robot ran low on battery, it left the station and another robot stepped in. That is the real factory signal: not just autonomy, but shift continuity. F.03 is rated for about 5 hours of runtime, so the 8-hour result depends on fleet orchestration, charging, and handoff. That matters more than a single clean demo. The stream was not perfect. There were pauses, hesitations, missed orientations, and small recovery moments. Good. A perfect short clip hides failure. An 8-hour livestream exposes the parts that actually matter: endurance, recovery, throughput, and whether the robot can stay useful after the novelty wears off. Figure says this was fully autonomous on Helix-02, with zero human intervention. For logistics and manufacturing, that is the threshold worth watching. Not “can it do one impressive task?” Can it keep doing the boring task for an entire shift? Figure is not showing a general human replacement yet. But for structured, repetitive factory work, the gap just got much smaller. The timing is also interesting: Figure says BotQ has already delivered 350+ F.03 units and reached a 1 robot/hour production cadence. And F.04 is now in full design lock, with parts starting to ship. The next test is obvious. 8 hours was the proof of endurance. 24/7 is the proof of labor economics.

RoboHub🤖

16,818 görüntüleme • 4 ay önce

TWO ROBOTS. ONE BEDROOM. 127 SECONDS. 🤖🛏️ They walked in, hung the jacket, cleared the desk, and made the bed together. No teleoperation. No voice commands. No script telling them who pulls which corner. Each one just watches the other — and adapts in real time. That clip is the video everyone watches. The money is not in the video. Figure units already rent to warehouses at ~$25 an hour — half a human shift. You keep the robot. The client keeps the flexibility. After the unit pays for itself, every hour is margin. Five ways regular people are already pulling cash from this boom — no factory, no engineering degree, no Tesla…
2:07

TWO ROBOTS. ONE BEDROOM. 127 SECONDS. 🤖🛏️ They walked in, hung the jacket, cleared the desk, and made the bed together. No teleoperation. No voice commands. No script telling them who pulls which corner. Each one just watches the other — and adapts in real time. That clip is the video everyone watches. The money is not in the video. Figure units already rent to warehouses at ~$25 an hour — half a human shift. You keep the robot. The client keeps the flexibility. After the unit pays for itself, every hour is margin. Five ways regular people are already pulling cash from this boom — no factory, no engineering degree, no Tesla…

DN_DEGEN

14,377 görüntüleme • 24 gün önce

⚠️ THIS ROBOT WOKE ITSELF UP IN A CARDBOARD BOX. NOBODY TOLD IT TO. A robot just unboxed itself. No hands. No engineers. No stage. No keynote. It woke up lying flat on its back inside a foam-lined shipping case in the middle of an ordinary office — desks, a small Christmas tree, nothing staged. Its legs bent upward, then extended, pushing it out of the case. It rolled, braced with its arms, lifted its torso, and stood up to full height right next to the open box it arrived in. Chinese subtitles ran the entire time as the robot calmly narrated its own startup: warning that it was about to move, asking not to be touched, confirming its position, then requesting that the packaging be cleared so it could start work. This is AGIBOT. The company that shipped more than 5,168 humanoid robots in 2025 — more than any competitor globally — and hit its 15,000th unit produced by mid-2026. Not a staged reveal. Not a product launch. Just a robot that ships itself in a box and gets up on its own. The unboxing used to be the boring part. Now it’s the demo.
0:36

⚠️ THIS ROBOT WOKE ITSELF UP IN A CARDBOARD BOX. NOBODY TOLD IT TO. A robot just unboxed itself. No hands. No engineers. No stage. No keynote. It woke up lying flat on its back inside a foam-lined shipping case in the middle of an ordinary office — desks, a small Christmas tree, nothing staged. Its legs bent upward, then extended, pushing it out of the case. It rolled, braced with its arms, lifted its torso, and stood up to full height right next to the open box it arrived in. Chinese subtitles ran the entire time as the robot calmly narrated its own startup: warning that it was about to move, asking not to be touched, confirming its position, then requesting that the packaging be cleared so it could start work. This is AGIBOT. The company that shipped more than 5,168 humanoid robots in 2025 — more than any competitor globally — and hit its 15,000th unit produced by mid-2026. Not a staged reveal. Not a product launch. Just a robot that ships itself in a box and gets up on its own. The unboxing used to be the boring part. Now it’s the demo.

DN_DEGEN

15,786 görüntüleme • 1 ay önce

Anton Leicht breaks down why the entire US strategic position is now a leveraged bet on winning AGI: "The US strategic position is a leveraged bet on building AGI. You can see that the production pace in China of all these military assets they would need for a great power conflict with the US is just outpacing the US by a lot." "On a lot of the metrics, China is winning. On the AI metrics specifically, the US is winning." "It's extremely difficult to pitch the US on the strategic idea that they should initiate a pause, slowdown, treaty, anything that has to do with AI specifically, when the US thinks this is the one way for us to get out of this. This is the one way to accelerate past all the other developments in China." "RSI is in a real way the strategic endpoint of the current structure of the US stock market and US strategic investment." "It seems very hard to do this unilateral disarmament around this one specific tool that seems to put the US ahead, and then not do something that also attaches to hypersonic missile production and drone coordination and all these things that in the trend favor China instead." Anton Leicht
2:29

Anton Leicht breaks down why the entire US strategic position is now a leveraged bet on winning AGI: "The US strategic position is a leveraged bet on building AGI. You can see that the production pace in China of all these military assets they would need for a great power conflict with the US is just outpacing the US by a lot." "On a lot of the metrics, China is winning. On the AI metrics specifically, the US is winning." "It's extremely difficult to pitch the US on the strategic idea that they should initiate a pause, slowdown, treaty, anything that has to do with AI specifically, when the US thinks this is the one way for us to get out of this. This is the one way to accelerate past all the other developments in China." "RSI is in a real way the strategic endpoint of the current structure of the US stock market and US strategic investment." "It seems very hard to do this unilateral disarmament around this one specific tool that seems to put the US ahead, and then not do something that also attaches to hypersonic missile production and drone coordination and all these things that in the trend favor China instead." Anton Leicht

MTS

10,697 görüntüleme • 2 ay önce

Robots from Humanoid passed real factory test at Siemens! 😮‍💨 Humanoid from the UK just completed a successful proof of concept with Siemens, deploying their HMND 01 wheeled humanoid robot in a real working factory. The task was simple but important: pick totes from a storage stack, transport them to a conveyor, and place them at the pickup point for human operators. Repeat until the stack is empty. The robot achieved 60 tote moves per hour, handled two different tote sizes, ran autonomously for more than 30 minutes at a time, stayed operational for over eight hours, and maintained over 90% success rate on pick and place tasks. This matters because it's not a demo video. It's a real deployment in Siemens' Electronics Factory in Erlangen, handling actual production work, measured against real operational metrics. The test ran in two phases. First, Humanoid built a physical twin in-house to test and optimize the system. Then they deployed on-site at Siemens for two weeks, where the robot operated in the real production environment. We can see a wheeled humanoid robot in action! So, now the ultimate question: wheels or legs? 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:26

Robots from Humanoid passed real factory test at Siemens! 😮‍💨 Humanoid from the UK just completed a successful proof of concept with Siemens, deploying their HMND 01 wheeled humanoid robot in a real working factory. The task was simple but important: pick totes from a storage stack, transport them to a conveyor, and place them at the pickup point for human operators. Repeat until the stack is empty. The robot achieved 60 tote moves per hour, handled two different tote sizes, ran autonomously for more than 30 minutes at a time, stayed operational for over eight hours, and maintained over 90% success rate on pick and place tasks. This matters because it's not a demo video. It's a real deployment in Siemens' Electronics Factory in Erlangen, handling actual production work, measured against real operational metrics. The test ran in two phases. First, Humanoid built a physical twin in-house to test and optimize the system. Then they deployed on-site at Siemens for two weeks, where the robot operated in the real production environment. We can see a wheeled humanoid robot in action! So, now the ultimate question: wheels or legs? 👀 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

21,993 görüntüleme • 7 ay önce

BREAKING: Eight Sleep is now available in mainland China. Our biggest expansion ever. A major company milestone. And a sign of where health technology is going. For more than a decade, we’ve engineered sleep technology that measures the body, adjusts the environment in real time, and improves sleep, not just tracks it. The future of health and longevity will not be built on data alone. It will be built on outcomes. That shift is happening around the world, and Eight Sleep is establishing itself as the leading global sleep brand. 300 million people in China suffer from sleep disorders. Average nightly sleep is 6.97 hours. The unmet need here is bigger than in any market we’ve entered. We’re excited for what’s ahead. Learn more at
1:04

BREAKING: Eight Sleep is now available in mainland China. Our biggest expansion ever. A major company milestone. And a sign of where health technology is going. For more than a decade, we’ve engineered sleep technology that measures the body, adjusts the environment in real time, and improves sleep, not just tracks it. The future of health and longevity will not be built on data alone. It will be built on outcomes. That shift is happening around the world, and Eight Sleep is establishing itself as the leading global sleep brand. 300 million people in China suffer from sleep disorders. Average nightly sleep is 6.97 hours. The unmet need here is bigger than in any market we’ve entered. We’re excited for what’s ahead. Learn more at

Matteo Franceschetti

3,045,162 görüntüleme • 5 ay önce

I need you to sit down for a moment and fully understand this: THE COUNTRY THAT SOLVES AI AND ROBOTICS WILL RULE THE WORLD AND SPACE. The west really only has Elon Musk, the east has 100s of companies fortified by an ENTIRE COUNTRY. Now some will argue no this is not true. No US company has the scale to MANUFACTURE, the compute power, and the finances to compete. Just a few hours ago we saw IRON for the first time, now you will. IRON, a 5’10, 150-lb AI humanoid robots are already building EV cars on the XPENG Motors factory floor. It has over 60 joints, a human-like spine, facial expressions, and male/female customizations The gait of this robot is the most human-like ever seen. Mass rollout in 2026. It is a very big deal. Because as the west does the best in clubbing each other over its head the last decade, China has looked and laughed and built at scale with a fortified government that has little diversion of goal, a 1000 year plan. The west has quietly plans and layers of lawyers and politicians. This is about where YOU LIVE and how you want to live. So when we kick the one person that is Atlas carrying our chance, in the groin, you make a choice on who’s world view you want. It is that simple. No, it is that simple. It ain’t no iPhone it is: whose’s world view will sustain. I can say no one is ready for what I have seen that is up for the next few years. You will think my bombastics were too tame.
7:10

I need you to sit down for a moment and fully understand this: THE COUNTRY THAT SOLVES AI AND ROBOTICS WILL RULE THE WORLD AND SPACE. The west really only has Elon Musk, the east has 100s of companies fortified by an ENTIRE COUNTRY. Now some will argue no this is not true. No US company has the scale to MANUFACTURE, the compute power, and the finances to compete. Just a few hours ago we saw IRON for the first time, now you will. IRON, a 5’10, 150-lb AI humanoid robots are already building EV cars on the XPENG Motors factory floor. It has over 60 joints, a human-like spine, facial expressions, and male/female customizations The gait of this robot is the most human-like ever seen. Mass rollout in 2026. It is a very big deal. Because as the west does the best in clubbing each other over its head the last decade, China has looked and laughed and built at scale with a fortified government that has little diversion of goal, a 1000 year plan. The west has quietly plans and layers of lawyers and politicians. This is about where YOU LIVE and how you want to live. So when we kick the one person that is Atlas carrying our chance, in the groin, you make a choice on who’s world view you want. It is that simple. No, it is that simple. It ain’t no iPhone it is: whose’s world view will sustain. I can say no one is ready for what I have seen that is up for the next few years. You will think my bombastics were too tame.

Brian Roemmele

446,861 görüntüleme • 10 ay önce

when we were at facebook, we believed that at some point in the future, most of the transactions on the internet would not be done by humans they would be done by machines that conviction shaped every architectural decision behind sui we built sui for the world we knew was coming a world where machines will be the primary economic actors on the internet and that world is no longer a forecast. it is unfolding right in front of us the internet has reached a tipping point where automated activity, supercharged by AI, now outpaces human interaction non-human traffic now accounts for more than 50% of all global web activity and you can see humans using agentic workflows more and more in their daily lives in the next years, that trend is going to grow exponentially and the volume of financial transactions executed by agents is also going to grow exponentially with it each agentic workload will be running multiple thousand economic transactions a second and this is going to be orders of magnitude higher than what human wallets do today the L1s optimized for human usage patterns, human attention, human accounts, and human patience cannot adapt to where this is going i have always said this if it is not in the foundation, you cannot patch your way to it later and rn, no other L1 has the foundation sui has this is why agentic apps like Beep, Audric, WaterX are choosing sui and this is just a start. more agentic apps will keep landing on sui because agents are optimizers. they will always route through the fastest, cheapest path on the internet and that path is sui we believed it at facebook. we believe it more today than we ever did the agentic economy is inevitable. and it will run on Sui
2:44

when we were at facebook, we believed that at some point in the future, most of the transactions on the internet would not be done by humans they would be done by machines that conviction shaped every architectural decision behind sui we built sui for the world we knew was coming a world where machines will be the primary economic actors on the internet and that world is no longer a forecast. it is unfolding right in front of us the internet has reached a tipping point where automated activity, supercharged by AI, now outpaces human interaction non-human traffic now accounts for more than 50% of all global web activity and you can see humans using agentic workflows more and more in their daily lives in the next years, that trend is going to grow exponentially and the volume of financial transactions executed by agents is also going to grow exponentially with it each agentic workload will be running multiple thousand economic transactions a second and this is going to be orders of magnitude higher than what human wallets do today the L1s optimized for human usage patterns, human attention, human accounts, and human patience cannot adapt to where this is going i have always said this if it is not in the foundation, you cannot patch your way to it later and rn, no other L1 has the foundation sui has this is why agentic apps like Beep, Audric, WaterX are choosing sui and this is just a start. more agentic apps will keep landing on sui because agents are optimizers. they will always route through the fastest, cheapest path on the internet and that path is sui we believed it at facebook. we believe it more today than we ever did the agentic economy is inevitable. and it will run on Sui

Adeniyi.sui

24,920 görüntüleme • 4 ay önce

Sunday Robotics' Tony Zhao runs a fully autonomous robot demo live and unscripted, and it corrects itself every time you mess with it: brexton: "I want to confirm for the audience right now that this is fully autonomous. There's no teleoperation, no one behind the curtain, and this is real time. And we did not prepare this demo before. Why do you think seeing real-time demos is so rare for robotics? What the audience is seeing right now is not that common." Tony Zhao: "In order for a live demo to work, it's really stressing all parts of the system. From the bottom is the reliability of the hardware, then the software system, then the model. Because we're a full-stack company, we're able to do excellent work across all of them. We have these robots running pretty much every day, and it just keeps getting better as they practice." brexton: "So kids can bump into Memo, people can drop clothes, and it will correct itself just on the fly." Tony Zhao: "Act Two is the first robotic policy that can handle the diversity of homes in a way that is this reliable. You can see as I'm twisting it, if I twist it in again, it will keep doing it. So Memo has infinite patience." Sunday
5:32

Sunday Robotics' Tony Zhao runs a fully autonomous robot demo live and unscripted, and it corrects itself every time you mess with it: brexton: "I want to confirm for the audience right now that this is fully autonomous. There's no teleoperation, no one behind the curtain, and this is real time. And we did not prepare this demo before. Why do you think seeing real-time demos is so rare for robotics? What the audience is seeing right now is not that common." Tony Zhao: "In order for a live demo to work, it's really stressing all parts of the system. From the bottom is the reliability of the hardware, then the software system, then the model. Because we're a full-stack company, we're able to do excellent work across all of them. We have these robots running pretty much every day, and it just keeps getting better as they practice." brexton: "So kids can bump into Memo, people can drop clothes, and it will correct itself just on the fly." Tony Zhao: "Act Two is the first robotic policy that can handle the diversity of homes in a way that is this reliable. You can see as I'm twisting it, if I twist it in again, it will keep doing it. So Memo has infinite patience." Sunday

MTS

134,855 görüntüleme • 1 ay önce

Elon just confirmed how long every working human has left before the robots take over. "AI will probably increase the global economy by 20 to 30%. That's my rough estimate. Meaning, on the order of 20 to 30 trillion per year." So that's a second United States economy appearing out of thin air, EVERY single year. And Elon's whole point is that the machines produce it, not the people. He even gave us the exact date for the digital half: "AI will be able to do anything digital, anything that does not require the shaping of atoms by hand, by the end of next year." By the end of next year... And on software specifically: "It's going to be impossible for a human to compete in writing software with AI." So every coder, every analyst, every job that lives on a screen is on a 12 to 18 month timer, straight from the richest man alive. But that's only the part that runs on electricity. And this is where it gets crazy... "There will be at least a billion robots in 10 years, and each will produce at least five times the output of a human." "The billion humanoid robots will be more productive than all humans combined." A billion machines, out-working ALL 8 billion of us. And he put a deadline on it: 10 years. And he even called that estimate small. So the version where robots out-produce the entire human race is the number he treats as safe. He said he'd bet serious money on it. But how does a billion of anything get built that fast? Robots building robots building robots. It starts slow and then it goes vertical. That’s how a few thousand becomes a billion. Elon also explained his own formula for how useful a robot actually is. He said it's the quality of the AI software, times the quality of the AI chip, times the dexterity of the hands. Software and chips are the exact things Elon and Nvidia have spent a decade making exponential. The third one is the hand. And the hand is the thing robotics has been stuck on for 40 years. A machine can crush the best human alive at chess and still can't pick a strange object off a messy table the way a toddler can. Grip, pressure, touch, knowing how hard to squeeze. That problem has barely moved while everything digital went vertical. The thing he named as the hard part is the exact thing his whole 10 year number depends on. So it all comes down to one variable, and it's the slowest-moving one in the entire machine: The robot hand. The brain is basically solved. The fingers have to catch up to it this decade, at planetary scale. Now to be fair, this is also where the most money on Earth is pointed right now. Tesla and a dozen others are throwing everything at exactly this problem. Elon's software calls tend to land but his atoms calls tend to fail. Because anything physical always takes longer than anything digital. He's also made this exact robot call before with wildly different numbers, 10 billion of them by 2040 in one speech, five per human in another. So here's the real question: Do you believe robot hands get solved inside 10 years? Because that one bet is the core of Elon‘s prediction. Everything else already came true.
1:39

Elon just confirmed how long every working human has left before the robots take over. "AI will probably increase the global economy by 20 to 30%. That's my rough estimate. Meaning, on the order of 20 to 30 trillion per year." So that's a second United States economy appearing out of thin air, EVERY single year. And Elon's whole point is that the machines produce it, not the people. He even gave us the exact date for the digital half: "AI will be able to do anything digital, anything that does not require the shaping of atoms by hand, by the end of next year." By the end of next year... And on software specifically: "It's going to be impossible for a human to compete in writing software with AI." So every coder, every analyst, every job that lives on a screen is on a 12 to 18 month timer, straight from the richest man alive. But that's only the part that runs on electricity. And this is where it gets crazy... "There will be at least a billion robots in 10 years, and each will produce at least five times the output of a human." "The billion humanoid robots will be more productive than all humans combined." A billion machines, out-working ALL 8 billion of us. And he put a deadline on it: 10 years. And he even called that estimate small. So the version where robots out-produce the entire human race is the number he treats as safe. He said he'd bet serious money on it. But how does a billion of anything get built that fast? Robots building robots building robots. It starts slow and then it goes vertical. That’s how a few thousand becomes a billion. Elon also explained his own formula for how useful a robot actually is. He said it's the quality of the AI software, times the quality of the AI chip, times the dexterity of the hands. Software and chips are the exact things Elon and Nvidia have spent a decade making exponential. The third one is the hand. And the hand is the thing robotics has been stuck on for 40 years. A machine can crush the best human alive at chess and still can't pick a strange object off a messy table the way a toddler can. Grip, pressure, touch, knowing how hard to squeeze. That problem has barely moved while everything digital went vertical. The thing he named as the hard part is the exact thing his whole 10 year number depends on. So it all comes down to one variable, and it's the slowest-moving one in the entire machine: The robot hand. The brain is basically solved. The fingers have to catch up to it this decade, at planetary scale. Now to be fair, this is also where the most money on Earth is pointed right now. Tesla and a dozen others are throwing everything at exactly this problem. Elon's software calls tend to land but his atoms calls tend to fail. Because anything physical always takes longer than anything digital. He's also made this exact robot call before with wildly different numbers, 10 billion of them by 2040 in one speech, five per human in another. So here's the real question: Do you believe robot hands get solved inside 10 years? Because that one bet is the core of Elon‘s prediction. Everything else already came true.

Ricardo

449,882 görüntüleme • 21 gün önce

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

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

Dustin

23,570 görüntüleme • 6 ay önce

John toured NIO's factory in China. They built an upscale EV for under $10k and went from the first shovel in the ground to the first car off the line in just 17 months. He said China knew it would always be behind in ICE cars, so it pushed aggressively into EVs to leapfrog to the next technology and gain an advantage over the rest of the world. "Going to their factory and seeing, number one, how quickly that factory is built. And second, the factory automation -- much of the process was done via robotics. Looking at the auto plants we have in the US, we still have a plant that was originally built a 100 years ago, operating outside of Chicago. The average age of a US plant is roughly 40 years now. They've been upgraded over time but I don't think they replicate what's happening with robotics in China. This combination of being able to do things really quickly with a skilled but low-cost labor force and robotics has just allowed China to create a quality product at a price that nobody in the rest of the world's really been able to figure out yet."
1:58

John toured NIO's factory in China. They built an upscale EV for under $10k and went from the first shovel in the ground to the first car off the line in just 17 months. He said China knew it would always be behind in ICE cars, so it pushed aggressively into EVs to leapfrog to the next technology and gain an advantage over the rest of the world. "Going to their factory and seeing, number one, how quickly that factory is built. And second, the factory automation -- much of the process was done via robotics. Looking at the auto plants we have in the US, we still have a plant that was originally built a 100 years ago, operating outside of Chicago. The average age of a US plant is roughly 40 years now. They've been upgraded over time but I don't think they replicate what's happening with robotics in China. This combination of being able to do things really quickly with a skilled but low-cost labor force and robotics has just allowed China to create a quality product at a price that nobody in the rest of the world's really been able to figure out yet."

Patrick OShaughnessy

50,988 görüntüleme • 6 ay önce

Marc Andreessen just incinerated 80 years of skepticism in under three minutes. Andreessen: “The four most dangerous words in investing are ‘this time is different.’” He’s talking about AI. And he’s about to detonate that phrase from the inside. For eight decades, artificial intelligence followed the same brutal script. Hype builds. Money floods in. The technology fails to deliver. The entire field collapses. In 1943, the first neural network paper proved mathematical models of brain cells could perform any logical computation. Revolutionary on paper. Dead on arrival. In 1956, scientists secured a grant to spend ten weeks at Dartmouth believing they could build AGI by the end of summer. They did not. In the 1980s, corporations poured over a billion dollars into “expert systems” designed to replicate human decision-making. By 1987, the entire market cratered. In 2016, machine learning hype surged again. Faded within months. Four waves. Four collapses. Same result every single time. The skeptics aren’t guessing. History is entirely on their side. Every generation of investors who believed “this time is different” got buried. But Andreessen isn’t finished. Andreessen: “I’ll tell you what’s different. Like, now it’s working.” That sentence sounds simple. It is the most consequential sentence in technology right now. AI didn’t make one breakthrough. It made four. Back to back. In the same window. Language models. Reasoning. Coding agents. Self-improvement. Every single one generating revenue in production right now. Not a demo. Not a research paper. Not a promise. Deployed infrastructure producing billions in real output today. Then the Linus Torvalds moment. Andreessen: “If Linus Torvalds is saying that the AI coding is now better than he is… that’s never happened before. And so now we know that it’s going to sweep through coding.” The man who built the operating system running most of the internet just admitted the machine writes better code than he does. That is not a marketing claim. That is surrender. And coding is the hardest test case. If AI can outperform the best human coder alive, everything downstream is already decided. Medicine. Law. Finance. Engineering. All derivatives. But the part that should unsettle you is the fourth breakthrough. Recursive self-improvement. The machine is no longer waiting for human engineers to upgrade it. It is researching, coding, and optimizing itself. The pace of improvement just decoupled from human biology entirely. And the hardware market is confirming something that has never happened in computing. Hardware is supposed to lose value the second it ships. Nvidia’s old chips are gaining value. Used silicon is appreciating like waterfront property. Every GPU on earth is sold out for the next three to four years. That is not a bubble. That is a structural shift in what the world physically needs to function. Andreessen: “I’m jumping out of my shoes. Like this is it. Like this is the culmination of 80 years worth of work and this is the time it’s becoming real.” Eighty years. Researchers spent entire careers chasing this problem and died before seeing it solved. Generations of scientists poured their finite lives into a theory that kept collapsing under its own promise. And now all four pieces arrived at once. The people calling this a bubble are running the same playbook that was correct every other time. But every other time, the technology wasn’t working. This time it is. For eighty years, “this time is different” buried everyone who believed it. This is the first time it buries everyone who doesn’t.
2:04

Marc Andreessen just incinerated 80 years of skepticism in under three minutes. Andreessen: “The four most dangerous words in investing are ‘this time is different.’” He’s talking about AI. And he’s about to detonate that phrase from the inside. For eight decades, artificial intelligence followed the same brutal script. Hype builds. Money floods in. The technology fails to deliver. The entire field collapses. In 1943, the first neural network paper proved mathematical models of brain cells could perform any logical computation. Revolutionary on paper. Dead on arrival. In 1956, scientists secured a grant to spend ten weeks at Dartmouth believing they could build AGI by the end of summer. They did not. In the 1980s, corporations poured over a billion dollars into “expert systems” designed to replicate human decision-making. By 1987, the entire market cratered. In 2016, machine learning hype surged again. Faded within months. Four waves. Four collapses. Same result every single time. The skeptics aren’t guessing. History is entirely on their side. Every generation of investors who believed “this time is different” got buried. But Andreessen isn’t finished. Andreessen: “I’ll tell you what’s different. Like, now it’s working.” That sentence sounds simple. It is the most consequential sentence in technology right now. AI didn’t make one breakthrough. It made four. Back to back. In the same window. Language models. Reasoning. Coding agents. Self-improvement. Every single one generating revenue in production right now. Not a demo. Not a research paper. Not a promise. Deployed infrastructure producing billions in real output today. Then the Linus Torvalds moment. Andreessen: “If Linus Torvalds is saying that the AI coding is now better than he is… that’s never happened before. And so now we know that it’s going to sweep through coding.” The man who built the operating system running most of the internet just admitted the machine writes better code than he does. That is not a marketing claim. That is surrender. And coding is the hardest test case. If AI can outperform the best human coder alive, everything downstream is already decided. Medicine. Law. Finance. Engineering. All derivatives. But the part that should unsettle you is the fourth breakthrough. Recursive self-improvement. The machine is no longer waiting for human engineers to upgrade it. It is researching, coding, and optimizing itself. The pace of improvement just decoupled from human biology entirely. And the hardware market is confirming something that has never happened in computing. Hardware is supposed to lose value the second it ships. Nvidia’s old chips are gaining value. Used silicon is appreciating like waterfront property. Every GPU on earth is sold out for the next three to four years. That is not a bubble. That is a structural shift in what the world physically needs to function. Andreessen: “I’m jumping out of my shoes. Like this is it. Like this is the culmination of 80 years worth of work and this is the time it’s becoming real.” Eighty years. Researchers spent entire careers chasing this problem and died before seeing it solved. Generations of scientists poured their finite lives into a theory that kept collapsing under its own promise. And now all four pieces arrived at once. The people calling this a bubble are running the same playbook that was correct every other time. But every other time, the technology wasn’t working. This time it is. For eighty years, “this time is different” buried everyone who believed it. This is the first time it buries everyone who doesn’t.

Dustin

18,103 görüntüleme • 5 ay önce

svt is telling us that they’re proud of their music combinations (classic and tech) but, they emphasize that the real maestro, who gives “command” in music is HUMAN! [EXPLANATION — 1] watch the clip where after wonjun fighting the human robots, maestro hoshi got captured jeonghan then made those human robots flew away and svt taking over the stage (previously occupied by robots) • the human robot soldiers get a notice “moving too fast”. this shows that human, are more capable than tech/robots (in this case, artistry) • notice that the dancers using robotic hands, shows the tech is a “tool” to help human, but the control is still in human itself
0:38

svt is telling us that they’re proud of their music combinations (classic and tech) but, they emphasize that the real maestro, who gives “command” in music is HUMAN! [EXPLANATION — 1] watch the clip where after wonjun fighting the human robots, maestro hoshi got captured jeonghan then made those human robots flew away and svt taking over the stage (previously occupied by robots) • the human robot soldiers get a notice “moving too fast”. this shows that human, are more capable than tech/robots (in this case, artistry) • notice that the dancers using robotic hands, shows the tech is a “tool” to help human, but the control is still in human itself

nuesvtws

900,100 görüntüleme • 2 yıl önce

WHAT IS AN AI "SOFTWARE FACTORY" AND IS IT HYPE (31 MINUTE BREAKDOWN) I think it's a silly name for a genuinely USEFUL idea! A software factory is 5-6 markdown files that sit next to your code and tell your agents how you like to work, so you can build high quality apps 24/7. It's going viral because AI coding has a trust problem. The model can build the feature, but with no structure around it you end up babysitting the agent, wondering what changed and hoping it didn't break something important. So you build with agents the same way a factory builds physical products! 1. Each feature gets its own station, which in software means its own branch, so multiple agents can work at the same time without stepping on each other. 2. The build station gives the agent rules for how to write the code, because "it works" is very different from "a developer could open this repo next month and understand what happened." 3. The proof station makes the agent show evidence. Screenshots, videos, speed numbers, before-and-after states. It has to prove the thing works instead of saying it works. 4. The review station runs the work through a code review agent, and if it doesn't clear the bar, it goes back through the line. 5. Then you show up at the end to merge. For a 100+ years people have run production this way, and it worked because the structure is good. The full episode on what’s a software factory is NOW live on The Startup Ideas Podcast (SIP) 🧃 with the wonderful Micky Watch: So is it hype?!? I don't think it is, because of what it does to your output! WITHOUT a factory, you build ONE feature at a time and you're the bottleneck at every step, prompting, checking the diff, testing it yourself, hoping nothing else broke (spoiler alert it often does). WITH a factory, EACH feature runs in its own isolated copy of the app, so you can have 10+ of them going at once, and each agent has to prove its own work and pass a code review before it ever reaches you. Instead of supervising the work, you're APPROVING finished work that already has evidence attached. REALLY interesting to see how work with agents is evolving to be….well, similar to working with people!
31:29

WHAT IS AN AI "SOFTWARE FACTORY" AND IS IT HYPE (31 MINUTE BREAKDOWN) I think it's a silly name for a genuinely USEFUL idea! A software factory is 5-6 markdown files that sit next to your code and tell your agents how you like to work, so you can build high quality apps 24/7. It's going viral because AI coding has a trust problem. The model can build the feature, but with no structure around it you end up babysitting the agent, wondering what changed and hoping it didn't break something important. So you build with agents the same way a factory builds physical products! 1. Each feature gets its own station, which in software means its own branch, so multiple agents can work at the same time without stepping on each other. 2. The build station gives the agent rules for how to write the code, because "it works" is very different from "a developer could open this repo next month and understand what happened." 3. The proof station makes the agent show evidence. Screenshots, videos, speed numbers, before-and-after states. It has to prove the thing works instead of saying it works. 4. The review station runs the work through a code review agent, and if it doesn't clear the bar, it goes back through the line. 5. Then you show up at the end to merge. For a 100+ years people have run production this way, and it worked because the structure is good. The full episode on what’s a software factory is NOW live on The Startup Ideas Podcast (SIP) 🧃 with the wonderful Micky Watch: So is it hype?!? I don't think it is, because of what it does to your output! WITHOUT a factory, you build ONE feature at a time and you're the bottleneck at every step, prompting, checking the diff, testing it yourself, hoping nothing else broke (spoiler alert it often does). WITH a factory, EACH feature runs in its own isolated copy of the app, so you can have 10+ of them going at once, and each agent has to prove its own work and pass a code review before it ever reaches you. Instead of supervising the work, you're APPROVING finished work that already has evidence attached. REALLY interesting to see how work with agents is evolving to be….well, similar to working with people!

GREG ISENBERG

30,112 görüntüleme • 8 gün önce

Larry Ellison just called AI the biggest thing in human history. He was being conservative. Ellison: “It is a much bigger deal than the industrial revolution, electricity, whatever. Everything that’s come before.” “Bigger” is the wrong word. “Bigger” assumes the same axis. A taller building on the same foundation. A faster car on the same road. This isn’t a taller building. This is a new dimension. Every revolution in human history extended the body. Steam replaced muscle. Electricity replaced fire. The combustion engine replaced the horse. Each one extraordinary. Each one civilization-altering. Each one built on an assumption nobody ever thought to question. That human cognition was the ceiling. A hammer builds nothing the carpenter can’t envision. A telescope reveals nothing the astronomer can’t interpret. A calculator solves nothing the mathematician can’t frame. 300,000 years of invention. Every tool a servant to the mind that forged it. AI ended that arrangement. Ellison: “We created neural networks that can answer questions that human brains would struggle with.” Not slower. Not less efficiently. Struggle with. We built something that thinks past the point where human thought stops. The tool is no longer bound by the toolmaker. Every ceiling humanity ever hit wasn’t physics. Wasn’t the universe setting limits. It was us. We were the boundary. And we just built something that doesn’t know it’s there. That’s not a bigger industrial revolution. That’s not even a revolution. That’s a species discovering it was the only thing standing between itself and everything it couldn’t yet imagine. And Ellison isn’t waiting for any of it. He’s already past AGI. Already framing superintelligence not as theory. As a scheduling problem. People hear that and reach for fear. Wrong instinct. Every prior revolution displaced labor. AI displaces limits. The industrial revolution didn’t make blacksmiths more creative. It made them irrelevant. AI inverts that. It doesn’t replace human cognition. It uncaps it. The kid with no teachers now has the most patient tutor ever built. The founder with no legal team now has one. The researcher at the edge of what one mind can hold now has a partner with no edge of its own. This isn’t automation. This is cognitive liberation. Every revolution before this answered a human question. This is the first one capable of asking its own. And we haven’t heard the first one yet.
1:17

Larry Ellison just called AI the biggest thing in human history. He was being conservative. Ellison: “It is a much bigger deal than the industrial revolution, electricity, whatever. Everything that’s come before.” “Bigger” is the wrong word. “Bigger” assumes the same axis. A taller building on the same foundation. A faster car on the same road. This isn’t a taller building. This is a new dimension. Every revolution in human history extended the body. Steam replaced muscle. Electricity replaced fire. The combustion engine replaced the horse. Each one extraordinary. Each one civilization-altering. Each one built on an assumption nobody ever thought to question. That human cognition was the ceiling. A hammer builds nothing the carpenter can’t envision. A telescope reveals nothing the astronomer can’t interpret. A calculator solves nothing the mathematician can’t frame. 300,000 years of invention. Every tool a servant to the mind that forged it. AI ended that arrangement. Ellison: “We created neural networks that can answer questions that human brains would struggle with.” Not slower. Not less efficiently. Struggle with. We built something that thinks past the point where human thought stops. The tool is no longer bound by the toolmaker. Every ceiling humanity ever hit wasn’t physics. Wasn’t the universe setting limits. It was us. We were the boundary. And we just built something that doesn’t know it’s there. That’s not a bigger industrial revolution. That’s not even a revolution. That’s a species discovering it was the only thing standing between itself and everything it couldn’t yet imagine. And Ellison isn’t waiting for any of it. He’s already past AGI. Already framing superintelligence not as theory. As a scheduling problem. People hear that and reach for fear. Wrong instinct. Every prior revolution displaced labor. AI displaces limits. The industrial revolution didn’t make blacksmiths more creative. It made them irrelevant. AI inverts that. It doesn’t replace human cognition. It uncaps it. The kid with no teachers now has the most patient tutor ever built. The founder with no legal team now has one. The researcher at the edge of what one mind can hold now has a partner with no edge of its own. This isn’t automation. This is cognitive liberation. Every revolution before this answered a human question. This is the first one capable of asking its own. And we haven’t heard the first one yet.

Dustin

14,852 görüntüleme • 3 ay önce

Bitwise CEO: There's a tempo mismatch that most crypto natives are missing. In crypto, "an hour is fast. A day is pretty fast. A week is a meaningful time frame, and nobody can remember what happened 4 weeks ago." But the mainstream investor now entering the space? For them a month is really fast and a year is a reasonable time frame. They move at a completely different pace. The progress is real - it just doesn't feel like it to people used to measuring time in hours. FT Hunter Horsley MR SHIFT 🦁 Bitwise.
1:50

Bitwise CEO: There's a tempo mismatch that most crypto natives are missing. In crypto, "an hour is fast. A day is pretty fast. A week is a meaningful time frame, and nobody can remember what happened 4 weeks ago." But the mainstream investor now entering the space? For them a month is really fast and a year is a reasonable time frame. They move at a completely different pace. The progress is real - it just doesn't feel like it to people used to measuring time in hours. FT Hunter Horsley MR SHIFT 🦁 Bitwise.

Milk Road

87,986 görüntüleme • 3 ay önce

This is the best video I have seen today. It made me cry and feel happy at the same time. Today, this NYC firefighter had the privilege of honoring the lives lost on September 11, 2001, by completing the 9/11 StairMaster Challenge. He was the only one doing it. He came straight after a 48-hour shift, still wearing his uniform and gear, and stepped onto the machine without making a show of it. No crowd. No announcement. Just a man carrying the weight of the day, and the weight of those stairs. Then a complete stranger named Nicole got on the StairMaster next to him. She put on a weight vest and stayed there so he would not have to climb alone. They both finished. This is the spirit of New Yorkers I remember from 25 years ago. Not the noise, not the swagger, not the version of the city that only exists in headlines. The real one. The one that shows up when no one is watching. Complete strangers who see someone carrying something heavy and quietly step beside them. People who do not ask for credit, do not wait to be invited, and do not look away. That is what true New Yorkers are about: showing up for one another, especially on the days when memory itself feels like a climb. Never forget. Never climb alone.
1:24

This is the best video I have seen today. It made me cry and feel happy at the same time. Today, this NYC firefighter had the privilege of honoring the lives lost on September 11, 2001, by completing the 9/11 StairMaster Challenge. He was the only one doing it. He came straight after a 48-hour shift, still wearing his uniform and gear, and stepped onto the machine without making a show of it. No crowd. No announcement. Just a man carrying the weight of the day, and the weight of those stairs. Then a complete stranger named Nicole got on the StairMaster next to him. She put on a weight vest and stayed there so he would not have to climb alone. They both finished. This is the spirit of New Yorkers I remember from 25 years ago. Not the noise, not the swagger, not the version of the city that only exists in headlines. The real one. The one that shows up when no one is watching. Complete strangers who see someone carrying something heavy and quietly step beside them. People who do not ask for credit, do not wait to be invited, and do not look away. That is what true New Yorkers are about: showing up for one another, especially on the days when memory itself feels like a climb. Never forget. Never climb alone.

I Meme Therefore I Am 🇺🇸

314,784 görüntüleme • 11 gün önce