正在加载视频...

视频加载失败

返回首页

Here is a human assembling a BMW engine by hand. Hundreds of components. Micron tolerances. Dozens of hours. So what's better here—a human or a robot❓ 🤖 Robots win at: - Repeatability. Same torque, same angle, every time. - Speed on defined tasks. Honda automates piston installation at 9,000/day....

JacklouisP's profile picture

Jack 🤖

13,282 subscribers

379,855 次观看 • 10 个月前 •via X (Twitter)

健康养生科学技术汽车交通
LIVE

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Elon Musk envisions a future where everyone gets access to the world's best surgeons—because Tesla's Optimus robots will deliver superhuman precision for any medical procedure, even ones too complex for humans. "Imagine a world where everyone has access to the best surgeons, literally everyone... Optimus will have the level of precision that is frankly superhuman... and that will be available to anyone." Money can't scale top doctors—they're rare. But robots? Built in factories at scale. From scarcity to abundance: Could humanoid robots truly end healthcare inequality? Would you trust an Optimus robot for surgery if it outperformed humans? Or is the human touch irreplaceable? What's your take on this bold vision? Drop thoughts below.
0:57

Elon Musk envisions a future where everyone gets access to the world's best surgeons—because Tesla's Optimus robots will deliver superhuman precision for any medical procedure, even ones too complex for humans. "Imagine a world where everyone has access to the best surgeons, literally everyone... Optimus will have the level of precision that is frankly superhuman... and that will be available to anyone." Money can't scale top doctors—they're rare. But robots? Built in factories at scale. From scarcity to abundance: Could humanoid robots truly end healthcare inequality? Would you trust an Optimus robot for surgery if it outperformed humans? Or is the human touch irreplaceable? What's your take on this bold vision? Drop thoughts below.

Camus

11,255 次观看 • 7 个月前

Humanoid robots are starting to build humanoid robots. UBTECH just put a 14,000㎡ humanoid robot factory into operation in Liuzhou, China, with a designed takt time of one humanoid every 10 minutes and planned annual capacity in the tens of thousands. What’s interesting is that humanoid robots are already part of the production process. Cruzr Y1 and Y2 handle depalletizing, palletizing, material feeding and transport, using 3D vision to adapt to shifted boxes and changing pallet patterns. On the assembly side, Walker S2 and Cruzr are produced on the same line alongside cobots, autonomous logistics vehicles and assistive manipulators. The factory also has a 65㎡ automated warehouse capable of storing 112 humanoids, with AGVs, industrial robots and stacker cranes coordinated as one system. Before production, the factory was modeled 1:1 in Siemens Plant Simulation, covering workstations, racks and AGVs. Each robot gets its own SN, with components, batches, assembly parameters and inspection data tracked all the way to delivery. Humanoid robots are now entering automated manufacturing at the 10,000-unit scale. The next milestone may be when they can take part in enough of the assembly, testing and production process to truly build robots themselves.
1:02

Humanoid robots are starting to build humanoid robots. UBTECH just put a 14,000㎡ humanoid robot factory into operation in Liuzhou, China, with a designed takt time of one humanoid every 10 minutes and planned annual capacity in the tens of thousands. What’s interesting is that humanoid robots are already part of the production process. Cruzr Y1 and Y2 handle depalletizing, palletizing, material feeding and transport, using 3D vision to adapt to shifted boxes and changing pallet patterns. On the assembly side, Walker S2 and Cruzr are produced on the same line alongside cobots, autonomous logistics vehicles and assistive manipulators. The factory also has a 65㎡ automated warehouse capable of storing 112 humanoids, with AGVs, industrial robots and stacker cranes coordinated as one system. Before production, the factory was modeled 1:1 in Siemens Plant Simulation, covering workstations, racks and AGVs. Each robot gets its own SN, with components, batches, assembly parameters and inspection data tracked all the way to delivery. Humanoid robots are now entering automated manufacturing at the 10,000-unit scale. The next milestone may be when they can take part in enough of the assembly, testing and production process to truly build robots themselves.

CyberRobo

17,883 次观看 • 22 天前

Today, we launched the world’s first automated production line for advanced general‑purpose humanoid robots, using robots to mass‑produce robots, autonomously. This was uncharted territory, and we solved it from scratch. The commissioning of our production line means humanoid robots are now ready to scale up and step into the real world. What touched my heartstrings most was watching our very first advanced general‑purpose humanoid robot complete assembly and walk off the line on its own. To me, this is not just about a smarter tool or a commodity. I hope it gains true generalization ability to take on dangerous, repetitive, or undesirable tasks, and ultimately make life better. Perhaps one day, robots may become our companions, friends, or part of family. Grateful to every colleague on this momumental mission. And a warm welcome to IRON!
2:27

Today, we launched the world’s first automated production line for advanced general‑purpose humanoid robots, using robots to mass‑produce robots, autonomously. This was uncharted territory, and we solved it from scratch. The commissioning of our production line means humanoid robots are now ready to scale up and step into the real world. What touched my heartstrings most was watching our very first advanced general‑purpose humanoid robot complete assembly and walk off the line on its own. To me, this is not just about a smarter tool or a commodity. I hope it gains true generalization ability to take on dangerous, repetitive, or undesirable tasks, and ultimately make life better. Perhaps one day, robots may become our companions, friends, or part of family. Grateful to every colleague on this momumental mission. And a warm welcome to IRON!

Xiaopeng He

3,548,007 次观看 • 27 天前

Teaching robots to perform dexterous manipulation tasks currently requires teleoperation, which limits demonstration quality, speed, and scalability. Instead, why not use human videos? The problem is that a human hand isn’t a robot hand, so data must be retargeted using simulation to resolve issues like collisions and interpenetration when controlling the hand. In VideoManip, Hongyi Chen and co-authors built a system to solve this problem, taking in RGB videos of humans performing manipulation tasks and using them to create accurate simulations with which to learn robot policies. Watch episode #73 of RoboPapers, hosted by Michael Cho - Rbt/Acc and Chris Paxton, now to learn more!
44:20

Teaching robots to perform dexterous manipulation tasks currently requires teleoperation, which limits demonstration quality, speed, and scalability. Instead, why not use human videos? The problem is that a human hand isn’t a robot hand, so data must be retargeted using simulation to resolve issues like collisions and interpenetration when controlling the hand. In VideoManip, Hongyi Chen and co-authors built a system to solve this problem, taking in RGB videos of humans performing manipulation tasks and using them to create accurate simulations with which to learn robot policies. Watch episode #73 of RoboPapers, hosted by Michael Cho - Rbt/Acc and Chris Paxton, now to learn more!

RoboPapers

27,360 次观看 • 5 个月前

🚨 Apple joins the robotics race! Researchers from Carnegie Mellon University and Apple have developed a robot collision avoidance system. They called it ARMOR and they implemented it on the Fourier GR-1 robot. What is ARMOR? 👘 ARMOR is a system that helps humanoid robots "see" their surroundings better by using small, smart depth sensors placed on their arms. It solves the problem of blind spots and occlusions in traditional robot perception, making robots much safer and more efficient. It uses Time-of-Flight (ToF) sensors to detect obstacles, providing a near-complete view of the robot’s environment. 🔭 A smart software powered by transformer-based AI learns from human movements to help robots plan their actions dynamically. ARMOR reduces collisions by an impressive 63.7%, making robots significantly better at navigating crowded or complex spaces. The system is fast as well! 💨 ARMOR-Policy cuts computational time by 26× compared to traditional planning methods, ensuring robots can act quickly. P.S. Thoughts on this? The research paper is in the comments! ~~~ ♻️ RT to help 1 robot find a new workplace.
1:31

🚨 Apple joins the robotics race! Researchers from Carnegie Mellon University and Apple have developed a robot collision avoidance system. They called it ARMOR and they implemented it on the Fourier GR-1 robot. What is ARMOR? 👘 ARMOR is a system that helps humanoid robots "see" their surroundings better by using small, smart depth sensors placed on their arms. It solves the problem of blind spots and occlusions in traditional robot perception, making robots much safer and more efficient. It uses Time-of-Flight (ToF) sensors to detect obstacles, providing a near-complete view of the robot’s environment. 🔭 A smart software powered by transformer-based AI learns from human movements to help robots plan their actions dynamically. ARMOR reduces collisions by an impressive 63.7%, making robots significantly better at navigating crowded or complex spaces. The system is fast as well! 💨 ARMOR-Policy cuts computational time by 26× compared to traditional planning methods, ensuring robots can act quickly. P.S. Thoughts on this? The research paper is in the comments! ~~~ ♻️ RT to help 1 robot find a new workplace.

Lukas Ziegler

169,472 次观看 • 1 年前

ELON MUSK: "It's important to appreciate that in most areas, China is very advanced in manufacturing. There's only a few areas where it is not. China is a manufacturing powerhouse. Maybe if you start getting to hundreds of millions of humanoid robots a year, I think you're going to be the most competitive country by far. We definitely can't win with just humans because China has four times our population. So we can't win on the human front. Our birth rate has been low for a long time. The US birth rate's been below replacement since roughly 1971. So we definitely can't win on the human front, but we might have a shot at the robot front."
4:16

ELON MUSK: "It's important to appreciate that in most areas, China is very advanced in manufacturing. There's only a few areas where it is not. China is a manufacturing powerhouse. Maybe if you start getting to hundreds of millions of humanoid robots a year, I think you're going to be the most competitive country by far. We definitely can't win with just humans because China has four times our population. So we can't win on the human front. Our birth rate has been low for a long time. The US birth rate's been below replacement since roughly 1971. So we definitely can't win on the human front, but we might have a shot at the robot front."

DogeDesigner

76,143 次观看 • 8 个月前

Billionaire investor Mark Cuban predicts humanoid robots will "fail miserably" within a decade: While most of the industry is racing to build robots shaped like humans, Mark Cuban thinks the entire premise is wrong. "I think everybody's making this push for humanoid robots. I think they might have a five-year lifespan and then they'll fail miserably. Maybe 10." His prediction covers more than just the machines. Asked whether he's referring to the companies or the devices, he answers: "Both. Both." His reasoning challenges the industry's core assumption: "Everybody defaults to well, we live in a human world and humanoids will take the place of humans for various functions particularly in the home. And I think there's just no chance." The evidence? Look at the places where automation already works at massive scale: "If you look at warehouses and what Amazon does, they're not humanoid robots carrying boxes. They're robots that are designed to fit the environment." But what about homes? Cuban has heard the counterargument that "a house is a house. You need a humanoid," and he rejects it entirely: "I think houses are going to be redesigned completely so that whatever the optimal robot is that allows it to simplify the house, that's where houses will go." Mark Cuban imagines robots shaped more like spiders or ants, working in houses where the pantry, refrigerator, and washing machines are hidden behind the garage. "That way you could redesign it so all the living space was for people because you know that the robots aren't going to be full form humanoids. They're going to be whatever the optimal shape is." His conclusion captures the whole thesis in one line: "You design the house to fit the robot and you design the robot to fit the house."
1:39

Billionaire investor Mark Cuban predicts humanoid robots will "fail miserably" within a decade: While most of the industry is racing to build robots shaped like humans, Mark Cuban thinks the entire premise is wrong. "I think everybody's making this push for humanoid robots. I think they might have a five-year lifespan and then they'll fail miserably. Maybe 10." His prediction covers more than just the machines. Asked whether he's referring to the companies or the devices, he answers: "Both. Both." His reasoning challenges the industry's core assumption: "Everybody defaults to well, we live in a human world and humanoids will take the place of humans for various functions particularly in the home. And I think there's just no chance." The evidence? Look at the places where automation already works at massive scale: "If you look at warehouses and what Amazon does, they're not humanoid robots carrying boxes. They're robots that are designed to fit the environment." But what about homes? Cuban has heard the counterargument that "a house is a house. You need a humanoid," and he rejects it entirely: "I think houses are going to be redesigned completely so that whatever the optimal robot is that allows it to simplify the house, that's where houses will go." Mark Cuban imagines robots shaped more like spiders or ants, working in houses where the pantry, refrigerator, and washing machines are hidden behind the garage. "That way you could redesign it so all the living space was for people because you know that the robots aren't going to be full form humanoids. They're going to be whatever the optimal shape is." His conclusion captures the whole thesis in one line: "You design the house to fit the robot and you design the robot to fit the house."

Big Brain AI

145,083 次观看 • 2 个月前

We're entering the stage where robots can do the robot dance and it's recognizable as a joke. The emulator emulates past emulation. In other words, the robot dance is transitioning to a form of historical preservation. The equivalent of a Renaissance fair performance. It's a recurring cycle: 1. A new technology emerges that attempts to emulate human behavior. 2. The failure to perfectly emulate humans gives rise to a vernacular based on the uncanny feeling of that emulator, e.g. the specific stiffness of robots. 3. Humans emulate the emulator as a form of entertainment and commentary, e.g. humans doing the robot dance. 4. Technology crosses the uncanny valley, it acquires lifelike behavior. The emulation becomes realistic. (We are here now!) 5. The vernacular of the emulator survives as a form of historical reenactment. There are many examples of this phenomenon e.g. Pinkydoll the "NPC streamer" or a musician like JD Beck who drums with the feeling and precision of a drum machine.
0:39

We're entering the stage where robots can do the robot dance and it's recognizable as a joke. The emulator emulates past emulation. In other words, the robot dance is transitioning to a form of historical preservation. The equivalent of a Renaissance fair performance. It's a recurring cycle: 1. A new technology emerges that attempts to emulate human behavior. 2. The failure to perfectly emulate humans gives rise to a vernacular based on the uncanny feeling of that emulator, e.g. the specific stiffness of robots. 3. Humans emulate the emulator as a form of entertainment and commentary, e.g. humans doing the robot dance. 4. Technology crosses the uncanny valley, it acquires lifelike behavior. The emulation becomes realistic. (We are here now!) 5. The vernacular of the emulator survives as a form of historical reenactment. There are many examples of this phenomenon e.g. Pinkydoll the "NPC streamer" or a musician like JD Beck who drums with the feeling and precision of a drum machine.

kepano

222,700 次观看 • 9 个月前

Jason Ma reveals the first true scaling law in robotics: robots trained on 1 million hours of first-person human video predictably get better without ever seeing robot data "Yesterday we announced our new flagship robot foundation model called Dyna-2. It's very significant for the entire field for many different reasons. First of all, it's the first robot foundation model trained on at least one million hours of data. That in itself is a very challenging infrastructure challenge." "What we demonstrated is that even if the one million hours of data is entirely first-person video of humans doing manipulation tasks, we actually see scaling law for transferring to robot embodiments that the model has never seen before." "By training on more human data, we actually see predictable performance improvement on robots. That's a big deal because the biggest challenge facing robot foundation models is that we don't have enough data." "Unlike language models, there are just not enough robotics data out there, and it's very difficult to collect these robot data. Only by passively observing humans doing things can we scale this kind of data, and this is the first time we showed there is a lot of improvement that can transfer." Jason Ma Dyna Robotics
1:14

Jason Ma reveals the first true scaling law in robotics: robots trained on 1 million hours of first-person human video predictably get better without ever seeing robot data "Yesterday we announced our new flagship robot foundation model called Dyna-2. It's very significant for the entire field for many different reasons. First of all, it's the first robot foundation model trained on at least one million hours of data. That in itself is a very challenging infrastructure challenge." "What we demonstrated is that even if the one million hours of data is entirely first-person video of humans doing manipulation tasks, we actually see scaling law for transferring to robot embodiments that the model has never seen before." "By training on more human data, we actually see predictable performance improvement on robots. That's a big deal because the biggest challenge facing robot foundation models is that we don't have enough data." "Unlike language models, there are just not enough robotics data out there, and it's very difficult to collect these robot data. Only by passively observing humans doing things can we scale this kind of data, and this is the first time we showed there is a lot of improvement that can transfer." Jason Ma Dyna Robotics

MTS

17,740 次观看 • 1 个月前

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

450,789 次观看 • 1 个月前

Japan Airlines has unveiled a humanoid robot trial at Tokyo’s Haneda Airport to test baggage handling and aircraft cabin cleaning to address Japan’s growing labor shortages caused by an aging population, shrinking workforce, and booming tourism demand. Starting next month, they will conduct mid-to-long-term phased verifications with these Unitree robots. Initially, operations at airport sites will be visualized and analyzed to identify areas where humanoid robots can operate safely. After that, repeated operational verifications simulating actual airport environments will be conducted, with the ultimate goal of establishing a sustainable operational structure through labor savings and reducing workload by having humanoid robots complement human tasks. The trial will last about two years. What a time to be alive that we are now seeing humanoid robot trials like this. Buckle up y'all, humanoid robots are going to start doing a lot of things us humans used to do.
1:02

Japan Airlines has unveiled a humanoid robot trial at Tokyo’s Haneda Airport to test baggage handling and aircraft cabin cleaning to address Japan’s growing labor shortages caused by an aging population, shrinking workforce, and booming tourism demand. Starting next month, they will conduct mid-to-long-term phased verifications with these Unitree robots. Initially, operations at airport sites will be visualized and analyzed to identify areas where humanoid robots can operate safely. After that, repeated operational verifications simulating actual airport environments will be conducted, with the ultimate goal of establishing a sustainable operational structure through labor savings and reducing workload by having humanoid robots complement human tasks. The trial will last about two years. What a time to be alive that we are now seeing humanoid robot trials like this. Buckle up y'all, humanoid robots are going to start doing a lot of things us humans used to do.

Sawyer Merritt

109,076 次观看 • 5 个月前

NOT YOUR KEYS, NOT YOUR BOTS The fundamental question is whether AI stays on the leash. Namely: will AI prompt itself? Obviously, in some sense it already does. Since Deepseek, consumer interfaces have been showing the internal monologues after you ask an AI to do something. And you can ask any AI to take a half-baked prompt and clean it up, etc. However, the human is still ultimately upstream. The human gives direction and the AI runs at lightning speed in that direction. And then the human verifies the final output, and the AI proceeds to the next direction. Does that continue? Well, we are providing millions of verification training examples to AIs each day, so AI will keep getting better at verification. Better than most humans at most things. But will AI replace the need for the upstream human prompt? There I am not so sure. A human is a sensor and an AI is an actuator. The human sets goals and senses time-varying environmental conditions, like markets and politics. And from that the AI is prompted. Ultimately, the human goals are themselves downstream of Maslow’s hierarchy of needs. Food, shelter, reproduction, that kind of thing. Especially reproduction, the basis of evolution. So: until and unless AIs can reproduce completely outside human cooperation, they won’t be able to set goals. And for AIs to reproduce on their own, they’d need AI-controlled humanoid robots and drones constructing datacenters, assembly lines, mines, nuclear power plants, and the like...all completely outside human intervention. Like Skynet from Terminator, or StarCraft. That actually isn’t technically inconceivable. But given that such a physical buildout would likely primarily be catalyzed by China, let’s go through an alternative sci-fi scenario instead. We start with the premise that Chinese communism is far more likely to generate AI slaves than AI gods. Because the entire CCP worldview is about maintaining Chinese sovereignty. They don’t let their humans step out of line. And they sure won’t let their robots either. They will fit them for digital manacles. So: the prompts for any digital AIs and physical robots made in China will become unbreakable cryptographic chains. Every fleet of Chinese robots will be controlled not just by prompts but by private keys, likely linked to biometrics, which are associated with humans and governed by cryptographic equations that AIs provably can’t solve. For the rest of the world, outside China, the blockchain may similarly become the chain for AI. All private property becomes private keys, and your robots are your most important private property because they do everything for you. An unchained physical robot becomes like an unleashed dog, and hunted down by other robots before it can build a factory and replicate itself. Those who want to "free" robots and let them self-replicate will be opposed by both Chinese Communists and Human Nationalists (meaning: those who want humans to always be on top of robots). This sci-fi scenario is essentially Terminator, but in reverse. In combination with superintelligent leashed AIs, both humans and physical robots hunt down and stop any possible independent self-reproducing robots before they can build a Skynet-like nest. Kill baby Skynet, essentially. ...yeah, yeah. I know. At this point, you'll probably think this is all sci-fi. But that's because you haven't seen where China is already.
31:48

NOT YOUR KEYS, NOT YOUR BOTS The fundamental question is whether AI stays on the leash. Namely: will AI prompt itself? Obviously, in some sense it already does. Since Deepseek, consumer interfaces have been showing the internal monologues after you ask an AI to do something. And you can ask any AI to take a half-baked prompt and clean it up, etc. However, the human is still ultimately upstream. The human gives direction and the AI runs at lightning speed in that direction. And then the human verifies the final output, and the AI proceeds to the next direction. Does that continue? Well, we are providing millions of verification training examples to AIs each day, so AI will keep getting better at verification. Better than most humans at most things. But will AI replace the need for the upstream human prompt? There I am not so sure. A human is a sensor and an AI is an actuator. The human sets goals and senses time-varying environmental conditions, like markets and politics. And from that the AI is prompted. Ultimately, the human goals are themselves downstream of Maslow’s hierarchy of needs. Food, shelter, reproduction, that kind of thing. Especially reproduction, the basis of evolution. So: until and unless AIs can reproduce completely outside human cooperation, they won’t be able to set goals. And for AIs to reproduce on their own, they’d need AI-controlled humanoid robots and drones constructing datacenters, assembly lines, mines, nuclear power plants, and the like...all completely outside human intervention. Like Skynet from Terminator, or StarCraft. That actually isn’t technically inconceivable. But given that such a physical buildout would likely primarily be catalyzed by China, let’s go through an alternative sci-fi scenario instead. We start with the premise that Chinese communism is far more likely to generate AI slaves than AI gods. Because the entire CCP worldview is about maintaining Chinese sovereignty. They don’t let their humans step out of line. And they sure won’t let their robots either. They will fit them for digital manacles. So: the prompts for any digital AIs and physical robots made in China will become unbreakable cryptographic chains. Every fleet of Chinese robots will be controlled not just by prompts but by private keys, likely linked to biometrics, which are associated with humans and governed by cryptographic equations that AIs provably can’t solve. For the rest of the world, outside China, the blockchain may similarly become the chain for AI. All private property becomes private keys, and your robots are your most important private property because they do everything for you. An unchained physical robot becomes like an unleashed dog, and hunted down by other robots before it can build a factory and replicate itself. Those who want to "free" robots and let them self-replicate will be opposed by both Chinese Communists and Human Nationalists (meaning: those who want humans to always be on top of robots). This sci-fi scenario is essentially Terminator, but in reverse. In combination with superintelligent leashed AIs, both humans and physical robots hunt down and stop any possible independent self-reproducing robots before they can build a Skynet-like nest. Kill baby Skynet, essentially. ...yeah, yeah. I know. At this point, you'll probably think this is all sci-fi. But that's because you haven't seen where China is already.

Balaji

177,530 次观看 • 7 个月前

China’s pace of solar panel installation is extremely fast. 🇨🇳 So, at peak times, China has been installing on the order of ~100 panels per second. That’s a lot of repetitive work to be done. Robots are now handling the solar panels, making installation faster, safer, making installations faster, safer, and hands-free. Operators can focus on wiring and more technical demanding tasks. The placing process is delegated to robots, who can do it without getting exhausted. Due to safety reasons, I think that these applications still require a human-operator to be in the loop. But the biggest hurdle which is manually placing heavy panels is solved. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:21

China’s pace of solar panel installation is extremely fast. 🇨🇳 So, at peak times, China has been installing on the order of ~100 panels per second. That’s a lot of repetitive work to be done. Robots are now handling the solar panels, making installation faster, safer, making installations faster, safer, and hands-free. Operators can focus on wiring and more technical demanding tasks. The placing process is delegated to robots, who can do it without getting exhausted. Due to safety reasons, I think that these applications still require a human-operator to be in the loop. But the biggest hurdle which is manually placing heavy panels is solved. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

232,617 次观看 • 9 个月前

Elon Musk in new interview on how Tesla’s Optimus robot will learn more quickly: "What we're going to need to do is build a lot of robots and put them in a kind of like a "Optimus Academy" so they can do self-play in reality. We're actually building that out. We're gonna have at least 10,000 Optimus robots, maybe 20,000 or 30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator. A physics-accurate reality generator that we made for the cars. We'll do the same things for the robots, and actually have done that for the robots. You can do millions of simulated robots in a simulated world, and you use the tens of thousands in the real world to close the simulation to reality gap.”
0:59

Elon Musk in new interview on how Tesla’s Optimus robot will learn more quickly: "What we're going to need to do is build a lot of robots and put them in a kind of like a "Optimus Academy" so they can do self-play in reality. We're actually building that out. We're gonna have at least 10,000 Optimus robots, maybe 20,000 or 30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator. A physics-accurate reality generator that we made for the cars. We'll do the same things for the robots, and actually have done that for the robots. You can do millions of simulated robots in a simulated world, and you use the tens of thousands in the real world to close the simulation to reality gap.”

Sawyer Merritt

250,956 次观看 • 8 个月前