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Chinese netizens' latest AI masterpiece: Their Terminator-style bot single-handedly wipes out a fleet of Tesla Optimus robots in epic simulation battle. Victory declared before breakfast 🇨🇳🤖 Musk, your move? 😂

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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.”
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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.”

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.Elon Musk told me he plans to build “Optimus Academy” to train an army of humanoid robots. > “millions of simulated robots in the simulated world” > “tens of thousands of robots in the real world, to close the simulation to reality gap.” Why? There’s two big differences between the way Tesla will train humanoid robots and the way it built Full Self-Driving. - FSD only requires learning three degrees of freedom: turning, accelerating, braking … and a humanoid robot has to learn how to coordinate 50+ joints. - You can sell a Tesla without FSD, which allows you to collect the millions and millions of hours of driving data needed to bootstrap your model ... but you can’t sell an Optimus that hasn’t learned how to do stuff yet. The Optimus Academy is Elon’s attempt to build the data flywheel that Tesla got for free with FSD.
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.Elon Musk told me he plans to build “Optimus Academy” to train an army of humanoid robots. > “millions of simulated robots in the simulated world” > “tens of thousands of robots in the real world, to close the simulation to reality gap.” Why? There’s two big differences between the way Tesla will train humanoid robots and the way it built Full Self-Driving. - FSD only requires learning three degrees of freedom: turning, accelerating, braking … and a humanoid robot has to learn how to coordinate 50+ joints. - You can sell a Tesla without FSD, which allows you to collect the millions and millions of hours of driving data needed to bootstrap your model ... but you can’t sell an Optimus that hasn’t learned how to do stuff yet. The Optimus Academy is Elon’s attempt to build the data flywheel that Tesla got for free with FSD.

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🔥🚀🤖ELON MUSK ON SENDING OPTIMUS ROBOTS TO MARS FIRST An early step in preparing the red planet for human arrival. “So the first flights there will send Optimus robots. We can go out there and explore, and kind of prepare the way for humans. That’ll be a very cool image if we’re able to achieve it… But that would be an epic picture to see Optimus walking around on the surface of Mars.” He's outlining a phased approach where robots handle initial risks and data collection. This minimizes human exposure to unknowns like landing challenges or environmental hazards. Why it matters: Starting with machines allows iterative improvements based on real Mars data, building confidence before crewed missions. It's a practical way to turn exploration into sustainable progress. Source: Elon Musk at SpaceX Starship Update, May 29, 2025 — Topic: Path to Mars

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Elon Musk says Tesla swallows 1.5 GB of video into 2 KB of control. "We really are photons in, controls out. That is the vast majority of your life: vision, photons in, and then motor controls out." Musk reduced the human nervous system to a single equation. That theory runs in every Tesla on the road. "Your Tesla is taking in one and a half gigabytes a second of video and outputting two kilobytes a second of control outputs with the video at 36 hertz and the control frequency at 18." A 750,000-to-1 compression ratio. The car decides which photons matter. "You don't care about the details of the leaves on the tree on the side of the road, but you care a lot about the road signs and the traffic lights, the pedestrians, and even whether someone in another car is looking at you or not looking at you." Then Musk extended the equation past Tesla. The same architecture runs Optimus. **Photons in. Controls out.** Different number of degrees of freedom. A car has steering and acceleration. A robot arm has dozens of joints. Same compression. More fingers on the other side. Musk, who built one Tesla AI engine across two products: "AI is mostly compression and correlation of two bitstreams." The implication: a human, a Tesla, and an Optimus all run the same loop. Musk, looking back at the human equation: "This is what happens with humans." If you're new here, GeniusThinking is a gallery for the greatest minds in economics, psychology, and history. Follow along for more similar content. P.S. I made a playbook breaking down 100+ mental models used by history's greatest thinkers. 5,000+ downloads. 113 five-star reviews. Comment "MODELS" + Follow GeniusThinking and I'll send it to you. — Elon Musk ( Elon Musk ), CEO of Tesla and SpaceX, on Dwarkesh Patel's ( Dwarkesh Patel ) podcast
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Elon Musk reveals Tesla is building a 30,000-robot academy where humanoids learn from each other. Cars were easy. Tesla had ten million on the road, beaming back driving data every second. But humanoid robots? There weren't ten million Optimi yet. There weren't ten. Robotics had run data-starved for decades. Tesla decided to fix it. You couldn't train a humanoid that had never been deployed. So Musk built a school for them instead. "We can have at least 10,000 Optimus robots, maybe 20-30,000, that are doing self-play and testing different tasks." Tesla called it the Optimus Academy. Picture a warehouse the size of a chip fab. Thirty thousand humanoid robots inside. Picking things up. Folding clothes. Walking. Tripping. Catching themselves. Failing in ways no human roboticist had thought to script. Each watching the others, learning what the human body shouldn't have made look easy. Every move generated a data point. Every failure generated a sample. Every robot taught every other robot. In simulation, Tesla could spin up a million robots overnight. But simulated physics lied about friction, slip, and drift. Real physics didn't. Cars learned from drivers. Optimi learned from each other. Each generation made the next one cheaper, faster, smarter. By the tenth generation, no human would recognize the curriculum. Recursive learning at electromechanical scale. Musk, on closing the loop: "You use the tens of thousands of robots in the real world to close the simulation to reality gap." Whoever opened the academy first owned the species. P.S. I made a playbook breaking down 100+ most powerful decision making mental models used by history's greatest thinkers. 5,000+ downloads. 113 five-star reviews. Grab a free copy here: If you're new here, follow GeniusThinking for content on the greatest minds in economics, psychology, and history. — Elon Musk ( Elon Musk ), CEO of Tesla and SpaceX, on Dwarkesh Patel's ( Dwarkesh Patel ) podcast

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136,427 görüntüleme • 2 ay önce

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Elon Musk: Tesla has no need to buy Uber. “There's no need [to buy Uber] because we have millions of cars that will be able to operate autonomously. And I should say that it's a combination of a Tesla-owned fleet and also enabling Tesla owners to be able to add or subtract their car to the fleet so that existing Tesla owners will be able to earn money by adding their car to the fleet for autonomous use. I think it's maybe possible for Tesla owners to make more in allowing the car to be added to the self-driving fleet then they cost them in the lease. And that's why I'd consider it sort of a business model that's similar to some combination of Airbnb and Uber. Just like Airbnb, you can rent out your spare bedroom or your house if you're not using it and make money on it. And that's what we expect Tesla customers to be able to do.” Interview with David Faber, May 20, 2025 Made and published via

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🇺🇸 ELON'S INTERSTELLAR PLAN: TESLA + SPACEX + xAI TO BUILD SUN-POWERED AI IN SPACE Elon is not just building companies anymore. He's building the actual infrastructure of the post-human era: Giant solar arrays + supercomputers orbiting the sun, powered by Tesla batteries/solar, launched by SpaceX, running xAI models. “I think that there's increasingly a convergence between SpaceX and Tesla and xAI in that if the future is solar-powered AI satellites. Which it pretty much needs to be in order to harness a non-trivial amount of the energy of the sun, you have to move to solar-powered AI satellites in deep space, which is a confluence of Tesla expertise and SpaceX expertise, and xAI on the AI front. It does feel like over time there's somewhat of a convergence there.” Then he flexed hard on Tesla: “We're making great progress with autonomous driving… You can literally download the Tesla app. Definitely try it out… We've made a lot of progress with electric vehicles, with battery packs and solar, and very much so with self-driving. Basically, real-world AI. Tesla is the world leader in real-world AI, I would say.” The 3 companies were never separate; they were always pieces of the same insane endgame. And Tesla's real-world AI (robots, cars, Optimus) is already the undisputed king. The convergence is happening right in front of us. Source: Nikhil Kamath, Elon Musk
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🇺🇸 ELON'S INTERSTELLAR PLAN: TESLA + SPACEX + xAI TO BUILD SUN-POWERED AI IN SPACE Elon is not just building companies anymore. He's building the actual infrastructure of the post-human era: Giant solar arrays + supercomputers orbiting the sun, powered by Tesla batteries/solar, launched by SpaceX, running xAI models. “I think that there's increasingly a convergence between SpaceX and Tesla and xAI in that if the future is solar-powered AI satellites. Which it pretty much needs to be in order to harness a non-trivial amount of the energy of the sun, you have to move to solar-powered AI satellites in deep space, which is a confluence of Tesla expertise and SpaceX expertise, and xAI on the AI front. It does feel like over time there's somewhat of a convergence there.” Then he flexed hard on Tesla: “We're making great progress with autonomous driving… You can literally download the Tesla app. Definitely try it out… We've made a lot of progress with electric vehicles, with battery packs and solar, and very much so with self-driving. Basically, real-world AI. Tesla is the world leader in real-world AI, I would say.” The 3 companies were never separate; they were always pieces of the same insane endgame. And Tesla's real-world AI (robots, cars, Optimus) is already the undisputed king. The convergence is happening right in front of us. Source: Nikhil Kamath, Elon Musk

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30,827 görüntüleme • 8 ay önce

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🚨 BREAKING NEWS; 🇺🇸 Elon Musk: Just launched another 60 Starlink satellites. While everyone is arguing on Earth, I am literally building a city on Mars. You guys are living in the past! 🚀🔴 🇨🇳 Xi Jinping: Elon, keep dreaming about Mars. While you were building rockets, we just built an AI quantum supercomputer that predicts what you'll tweet 5 minutes before you even think it! 🤖🧠 🇺🇸 Elon Musk: Cute! But can your AI land a rocket back on a drone ship in the middle of the ocean, or does it just ban memes of Winnie the Pooh? 🎯🛥️ 🇨🇳 Xi Jinping: Our AI doesn't need to land rockets, Elon. It just bought 51% of your Twitter stock while you were typing that reply! 📈💰📉

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🇨🇳YOUR ONLINE FLIRT MIGHT BE A TRAFFICKED SLAVE IN A CHINESE SCAM CAMP Thought the person who sent you a funny message on WhatsApp is an evil crook munching popcorn while lying about their gender? Try a trafficking victim locked in a prison-style compound in Cambodia, Laos, or Myanmar, forced by Chinese crime syndicates to run romance scams or get beaten, starved, or electrocuted. Tens of thousands are trapped like this, scamming the West so gang bosses can cash out. The Chinese authorities? Probably not too interested if the scams aren't landing in Russia... Source: Julian Morgans on IG

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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

177,058 görüntüleme • 6 ay önce

Demystifying China's Dancing Robots: How Did They Catch Handkerchiefs?🇨🇳🤖 16 humanoid robots from Chinese robotics company, Unitree, took center stage at the annual #SpringFestivalGala. The robots seamlessly coordinated with 16 human dancers to perform a traditional Yangko dance, a vibrant folk art form from northeast China, blending cultural heritage with cutting-edge technology. One of the most captivating moments came when the robots showcased their ability to manipulate handkerchiefs, a signature element of Yangko dance. With precise mechanical arm movements, the robots sent the handkerchiefs twirling and soaring through the air, creating a dazzling visual spectacle that symbolized the perfect fusion of tradition and modernity. To maintain the stable upright standing position is already a challenge for current humanoid robots – consider the shaky steps and tendency to roll off even a small incline of Elon Musk's Optimus. To toss a handkerchief and catch it back in place requires the integration of sensors, algorithm and smart design. "We've designed a very clever mechanism that integrates multiple AI control algorithms. There are two motors at the end of the robotic arm: one maintains a high-speed spinning motion, while the other ensures that the handkerchief can be thrown out and then retracted," Unitree's marketing representative said. The 16 humanoid robots belong to Unitree's H1 series, nicknamed Fuxi. Standing at 1.8 meters tall and weighing 47 kilograms, the robots took the stage at the Spring Festival Gala stage over a year after debuting in August 2023. They also attended the NVIDIA GTC conference in 2024. #ChineseNewYear #DeepSeek (Link:
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Demystifying China's Dancing Robots: How Did They Catch Handkerchiefs?🇨🇳🤖 16 humanoid robots from Chinese robotics company, Unitree, took center stage at the annual #SpringFestivalGala. The robots seamlessly coordinated with 16 human dancers to perform a traditional Yangko dance, a vibrant folk art form from northeast China, blending cultural heritage with cutting-edge technology. One of the most captivating moments came when the robots showcased their ability to manipulate handkerchiefs, a signature element of Yangko dance. With precise mechanical arm movements, the robots sent the handkerchiefs twirling and soaring through the air, creating a dazzling visual spectacle that symbolized the perfect fusion of tradition and modernity. To maintain the stable upright standing position is already a challenge for current humanoid robots – consider the shaky steps and tendency to roll off even a small incline of Elon Musk's Optimus. To toss a handkerchief and catch it back in place requires the integration of sensors, algorithm and smart design. "We've designed a very clever mechanism that integrates multiple AI control algorithms. There are two motors at the end of the robotic arm: one maintains a high-speed spinning motion, while the other ensures that the handkerchief can be thrown out and then retracted," Unitree's marketing representative said. The 16 humanoid robots belong to Unitree's H1 series, nicknamed Fuxi. Standing at 1.8 meters tall and weighing 47 kilograms, the robots took the stage at the Spring Festival Gala stage over a year after debuting in August 2023. They also attended the NVIDIA GTC conference in 2024. #ChineseNewYear #DeepSeek (Link:

Li Jingjing 李菁菁

11,169 görüntüleme • 1 yıl önce

🚨 This might be the most important Tesla to Mars - The Podcast podcast episode we've ever recorded. One of many to come... If you're even slightly curious about how Tesla will change the world.. This is where the robotaxi countdown begins. 👇 We dive into: 🚗 Why Tesla's Robotaxi strategy is more than just ride-hailing 💰 The economics of turning cars into cash machines 📉 Why your used Tesla might be more valuable than you think 🤖 How humanoid robots (Optimus) fit into the fleet 🌀 The Doge Flywheel, data monetization, edge AI, and the age of abundance 📈 Real-world insights from MisterGreen’s 5,000-vehicle fleet 🧭 How YOU can position yourself before the tidal wave hits This episode isn’t just about cars. It’s about what happens when intelligence, mobility, and automation converge. The future is being built and it's faster than most realize. If you want to be ahead of the curve… This is where to start! 🔗 to full YT video in the comments below. Let me know what you think! And if you wanna join, hit me up!
0:38

🚨 This might be the most important Tesla to Mars - The Podcast podcast episode we've ever recorded. One of many to come... If you're even slightly curious about how Tesla will change the world.. This is where the robotaxi countdown begins. 👇 We dive into: 🚗 Why Tesla's Robotaxi strategy is more than just ride-hailing 💰 The economics of turning cars into cash machines 📉 Why your used Tesla might be more valuable than you think 🤖 How humanoid robots (Optimus) fit into the fleet 🌀 The Doge Flywheel, data monetization, edge AI, and the age of abundance 📈 Real-world insights from MisterGreen’s 5,000-vehicle fleet 🧭 How YOU can position yourself before the tidal wave hits This episode isn’t just about cars. It’s about what happens when intelligence, mobility, and automation converge. The future is being built and it's faster than most realize. If you want to be ahead of the curve… This is where to start! 🔗 to full YT video in the comments below. Let me know what you think! And if you wanna join, hit me up!

Kees Roelandschap

13,777 görüntüleme • 1 yıl önce

🇨🇳 China opened a real school for robots, and the first class of 30 is already enrolled. The Hangzhou facility puts humanoid “students” through physical check-ups, specialized coursework, and a final skills exam before handing them official certificates. Tracks cover industrial work, security, customer service, entertainment, and even medicine and the arts. Once they pass, the robots are sent straight into real jobs. This is more than a gimmick. China is racing to move humanoids out of demo halls and into the actual workforce. The school standardizes training so the same software and skills can be copied across machines, speeding up deployment. In a country already pushing hard on embodied AI, teaching robots how to hold a job is the next logical step. Writer: Lucas
2:24

🇨🇳 China opened a real school for robots, and the first class of 30 is already enrolled. The Hangzhou facility puts humanoid “students” through physical check-ups, specialized coursework, and a final skills exam before handing them official certificates. Tracks cover industrial work, security, customer service, entertainment, and even medicine and the arts. Once they pass, the robots are sent straight into real jobs. This is more than a gimmick. China is racing to move humanoids out of demo halls and into the actual workforce. The school standardizes training so the same software and skills can be copied across machines, speeding up deployment. In a country already pushing hard on embodied AI, teaching robots how to hold a job is the next logical step. Writer: Lucas

Mario Nawfal

57,446 görüntüleme • 10 gün önce

🇨🇳 China has demonstrated another computer simulation using the Zhutian reconnaissance-strike drone, capable of carrying up to 100 small kamikaze drones. 1. In the first case, it shows how a swarm of kamikazes is launched from a drone in the airspace over the Chinese province of Fujian to disable Taiwan's air defense systems, initially already knowing their location and capabilities. 2. In the second case, strikes are carried out against the US Navy's aircraft carrier strike group in the Pacific Ocean and its deck-based aircraft. Due to the large number of kamikazes, a breakthrough in American air defense is achieved. It's clear that in the simulation, so many drones cannot carry kamikazes at once. It's likely that in the case of real combat use, up to a squadron of 12 Zhutian drones will be simultaneously launched into the air. See the latest updates with us: Visioner
2:51

🇨🇳 China has demonstrated another computer simulation using the Zhutian reconnaissance-strike drone, capable of carrying up to 100 small kamikaze drones. 1. In the first case, it shows how a swarm of kamikazes is launched from a drone in the airspace over the Chinese province of Fujian to disable Taiwan's air defense systems, initially already knowing their location and capabilities. 2. In the second case, strikes are carried out against the US Navy's aircraft carrier strike group in the Pacific Ocean and its deck-based aircraft. Due to the large number of kamikazes, a breakthrough in American air defense is achieved. It's clear that in the simulation, so many drones cannot carry kamikazes at once. It's likely that in the case of real combat use, up to a squadron of 12 Zhutian drones will be simultaneously launched into the air. See the latest updates with us: Visioner

Visioner

58,832 görüntüleme • 8 ay önce

TESLA: Is the major growth behind the company - or ahead of it?? That is always an important question to ask. But Tesla has Elon Musk. And Elon Musk thinks at scales that might cause other CEO’s brains to short-circuit. While they are planning a flashy product demo; Elon Musk is planning for: ♦️ A BILLION AI Chips ♦️100 MILLION Robots ♦️A Terawatt of Power Plans this big require vertical integration; an obsessive focus on locking down supply chains (moving suppliers to YOUR timeline); and removing all obstacles, unnecessary parts or processes —especially when the full ecosystem must align to deliver at this scale. Plans this big can dwarf Tesla’s 43% compounded returns to date. Spectacular which made Larry Fink suggest you should invest in growth, specifically in Elon Musk. Spectacular returns which Larry Fink contrasted to Blackrock’s own returns of ~21%. ♦️Do you think Elon Musk can do it? I follow the infrastructure moves closely — ground broken on the Terafab research fab lab, industrial machines being ordered, job listings for chip experts in Seoul and Taiwan, and the Optimus line taking over the Model S/X floor space in Fremont. ♦️My answer is Elon Musk ALREADY IS. Doubters can get out of his way. Elon Musk will bend reality to achieve his ambition.
1:05

TESLA: Is the major growth behind the company - or ahead of it?? That is always an important question to ask. But Tesla has Elon Musk. And Elon Musk thinks at scales that might cause other CEO’s brains to short-circuit. While they are planning a flashy product demo; Elon Musk is planning for: ♦️ A BILLION AI Chips ♦️100 MILLION Robots ♦️A Terawatt of Power Plans this big require vertical integration; an obsessive focus on locking down supply chains (moving suppliers to YOUR timeline); and removing all obstacles, unnecessary parts or processes —especially when the full ecosystem must align to deliver at this scale. Plans this big can dwarf Tesla’s 43% compounded returns to date. Spectacular which made Larry Fink suggest you should invest in growth, specifically in Elon Musk. Spectacular returns which Larry Fink contrasted to Blackrock’s own returns of ~21%. ♦️Do you think Elon Musk can do it? I follow the infrastructure moves closely — ground broken on the Terafab research fab lab, industrial machines being ordered, job listings for chip experts in Seoul and Taiwan, and the Optimus line taking over the Model S/X floor space in Fremont. ♦️My answer is Elon Musk ALREADY IS. Doubters can get out of his way. Elon Musk will bend reality to achieve his ambition.

Amy

12,507 görüntüleme • 3 ay önce

Data has always been the bottleneck for physical AI in self driving and robotics. Tesla is taking two very different approaches for FSD and Optimus. Tesla’s Optimus Training Playbook: 1. Build 30k Optimus Gen 3 robots 2. Operate them in a mock environment where they can perform self-play “Optimus Academy” 3. Train in sim using the real robot data to close sim2real gap. Tesla FSD Training Playbook: 1. Sell millions of cars outfitted with cheap cameras 2. Collect diverse real world driving data (especially intervention and failure recovery data) for free as a byproduct of customers driving the cars. 3. Use driving data to train Autopilot/FSD and deploy policies incrementally as a supervised FSD product 4. Repeat until policy reaches robust unsupervised full self driving for robotaxi launch. The Tesla FSD playbook is a beautiful self-funding, customer subsidized, diverse real world data flywheel. The Optimus playbook is the opposite and shares none of the beautiful attributes of the FSD training flywheel that made FSD successful. The key differences: 1. Instead of having customers pay you for vehicles, Tesla will need to fund 30,000 Optimus robots. Assuming the current landed cost per unit is $100k, that will be $3B to build plus another ~30% per year for maintenance labor and spare parts given it’s still an unhardened pre-production prototype is another $900M per year. For reference, Tesla’s GAAP net income in 2025 was $3.8B. 2. Instead of having customers drive their Teslas on roads all across the world giving Tesla an insanely rich and diverse dataset that Waymo and other AV companies could never collect, the Optimus Academy is doing the equivalent of building a fake town in a parking lot and driving their car in that parking lot. No matter how real you try to make the environments for self-play you can never replicate the diversity, complexity and failure modes of the real world. Data collected in staged environments produces demo-grade policies and will not be rich enough to generalize to the vast diversity of environments, tasks, objects, etc. out of distribution. 3. Instead of having customers collect real world failure recovery data (DAgger style) for free every time FSD disengages, the Optimus Academy will need paid teleoperators or onsite operators to collect the recovery data. Assuming 1 person can manage 2 robots to start that would cost $3.5B in labor per year (30,000 robots, $40/hr fully loaded, 16 hrs/day, 365 days per year, 2:1 robot:operator). Tesla can come up with the money to do this but money doesn’t solve the “mock data” problem. Given the higher degrees of freedom in humanoids vs. cars, training a generalized humanoid will be harder and require more data than a self-driving vehicle. The best way to train your robot is by deploying them in the diverse real world, subsidized by real customer operations. Humanoids face a chicken and egg where it’s very hard to bootstrap your way to a first policy that’s good enough to deploy in real production environments. This is an extremely capital intensive playbook (which doesn’t even include cost of training). Time will tell if it works but a better playbook would be finding a way to copy the FSD playbook.
1:54

Data has always been the bottleneck for physical AI in self driving and robotics. Tesla is taking two very different approaches for FSD and Optimus. Tesla’s Optimus Training Playbook: 1. Build 30k Optimus Gen 3 robots 2. Operate them in a mock environment where they can perform self-play “Optimus Academy” 3. Train in sim using the real robot data to close sim2real gap. Tesla FSD Training Playbook: 1. Sell millions of cars outfitted with cheap cameras 2. Collect diverse real world driving data (especially intervention and failure recovery data) for free as a byproduct of customers driving the cars. 3. Use driving data to train Autopilot/FSD and deploy policies incrementally as a supervised FSD product 4. Repeat until policy reaches robust unsupervised full self driving for robotaxi launch. The Tesla FSD playbook is a beautiful self-funding, customer subsidized, diverse real world data flywheel. The Optimus playbook is the opposite and shares none of the beautiful attributes of the FSD training flywheel that made FSD successful. The key differences: 1. Instead of having customers pay you for vehicles, Tesla will need to fund 30,000 Optimus robots. Assuming the current landed cost per unit is $100k, that will be $3B to build plus another ~30% per year for maintenance labor and spare parts given it’s still an unhardened pre-production prototype is another $900M per year. For reference, Tesla’s GAAP net income in 2025 was $3.8B. 2. Instead of having customers drive their Teslas on roads all across the world giving Tesla an insanely rich and diverse dataset that Waymo and other AV companies could never collect, the Optimus Academy is doing the equivalent of building a fake town in a parking lot and driving their car in that parking lot. No matter how real you try to make the environments for self-play you can never replicate the diversity, complexity and failure modes of the real world. Data collected in staged environments produces demo-grade policies and will not be rich enough to generalize to the vast diversity of environments, tasks, objects, etc. out of distribution. 3. Instead of having customers collect real world failure recovery data (DAgger style) for free every time FSD disengages, the Optimus Academy will need paid teleoperators or onsite operators to collect the recovery data. Assuming 1 person can manage 2 robots to start that would cost $3.5B in labor per year (30,000 robots, $40/hr fully loaded, 16 hrs/day, 365 days per year, 2:1 robot:operator). Tesla can come up with the money to do this but money doesn’t solve the “mock data” problem. Given the higher degrees of freedom in humanoids vs. cars, training a generalized humanoid will be harder and require more data than a self-driving vehicle. The best way to train your robot is by deploying them in the diverse real world, subsidized by real customer operations. Humanoids face a chicken and egg where it’s very hard to bootstrap your way to a first policy that’s good enough to deploy in real production environments. This is an extremely capital intensive playbook (which doesn’t even include cost of training). Time will tell if it works but a better playbook would be finding a way to copy the FSD playbook.

Simon Kalouche

34,671 görüntüleme • 6 ay önce