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Welding robots. The original use case for industrial automation—first deployed in the 1960s at GM. 60 years later, they dominate automotive body shops. Hundreds of robots in perfect sync, laying thousands of spot welds per vehicle. But step outside high-volume production and they're rare. Most fab shops still weld...

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Elon Musk: "We’re in the final stages of completion of Optimus 3, which is really going to be by far the most advanced robot in the world, nothing's even close. In fact, I haven’t even sent any demos of robots that are as good as Optimus 3, frankly. We’ll start production on Optimus 3 this summer, but very slow at first. And then probably reach high-volume production around summer next year. We’ll have Optimus 4 design complete by next year like, we will try to release a new robot design every year, an improved robot design every year."
0:53

Elon Musk: "We’re in the final stages of completion of Optimus 3, which is really going to be by far the most advanced robot in the world, nothing's even close. In fact, I haven’t even sent any demos of robots that are as good as Optimus 3, frankly. We’ll start production on Optimus 3 this summer, but very slow at first. And then probably reach high-volume production around summer next year. We’ll have Optimus 4 design complete by next year like, we will try to release a new robot design every year, an improved robot design every year."

Mars University

201,234 Aufrufe • vor 29 Tagen

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
1:04

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

GeniusThinking

136,378 Aufrufe • vor 1 Monat

Elon Musk: Most engineering is done with people who don’t have PhDs. You don’t need a PhD for that — but you do need competent personnel. Right now, Tesla is pedal to the metal, going as fast as possible to get AI5 chip design into production, reach full scale, and secure every chip fab we possibly can. If everything goes at maximum speed, AI5 will reach production around the second quarter of next year, and then AI6 would hopefully follow less than a year later. We are using TSMC Taiwan, Samsung Korea, TSMC Arizona, and Samsung Texas — and even after securing all of that, we still don’t have enough capacity. When you ask, “What’s the timeframe to reach volume production?” the answer is: You’ve got to build the fab, start production, climb the yield curve, and reach high-yield volume production — and that takes about 5 years.
1:43

Elon Musk: Most engineering is done with people who don’t have PhDs. You don’t need a PhD for that — but you do need competent personnel. Right now, Tesla is pedal to the metal, going as fast as possible to get AI5 chip design into production, reach full scale, and secure every chip fab we possibly can. If everything goes at maximum speed, AI5 will reach production around the second quarter of next year, and then AI6 would hopefully follow less than a year later. We are using TSMC Taiwan, Samsung Korea, TSMC Arizona, and Samsung Texas — and even after securing all of that, we still don’t have enough capacity. When you ask, “What’s the timeframe to reach volume production?” the answer is: You’ve got to build the fab, start production, climb the yield curve, and reach high-yield volume production — and that takes about 5 years.

Ian Miles Cheong

92,034 Aufrufe • vor 5 Monaten

Robot dogs are now welders! 👨🏼‍🏭 Path Robotics launches a mobile welding robot on quadruped platform, called Rove. This quadruped robotic welding system is paired with their Obsidian physical AI model. Obsidian already delivers autonomous, adaptive welding inside fixed cells. Rove brings intelligent welding to the part rather than moving the part to a fixed workstation. Shipbuilding, heavy construction, and large-scale fabrication share a constraint, massive assemblies and workpieces that cannot be moved or fixtured inside welding cells. These conditions have limited welding automation in environments that need it most, just as skilled welder shortages reach critical levels. Legged robots have long been considered too unstable for precision welding. Rove changes that. Obsidian provides the perception and adaptability needed to operate in high-variability environments. Saronic Technologies, a leader in autonomous maritime vessels, is one of the first early adopters, integrating Rove into its physical AI-powered shipbuilding operations in Franklin, Louisiana. 🇺🇸 Welding requires millimeter-level precision on a moving quadruped platform, considered impossible until AI-based perception and control made it feasible. 🔥 Andrew Lonsberry gotta be honest, but a welding robot dog wasn't on bingo card for 2026. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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Robot dogs are now welders! 👨🏼‍🏭 Path Robotics launches a mobile welding robot on quadruped platform, called Rove. This quadruped robotic welding system is paired with their Obsidian physical AI model. Obsidian already delivers autonomous, adaptive welding inside fixed cells. Rove brings intelligent welding to the part rather than moving the part to a fixed workstation. Shipbuilding, heavy construction, and large-scale fabrication share a constraint, massive assemblies and workpieces that cannot be moved or fixtured inside welding cells. These conditions have limited welding automation in environments that need it most, just as skilled welder shortages reach critical levels. Legged robots have long been considered too unstable for precision welding. Rove changes that. Obsidian provides the perception and adaptability needed to operate in high-variability environments. Saronic Technologies, a leader in autonomous maritime vessels, is one of the first early adopters, integrating Rove into its physical AI-powered shipbuilding operations in Franklin, Louisiana. 🇺🇸 Welding requires millimeter-level precision on a moving quadruped platform, considered impossible until AI-based perception and control made it feasible. 🔥 Andrew Lonsberry gotta be honest, but a welding robot dog wasn't on bingo card for 2026. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

10,227 Aufrufe • vor 3 Monaten

A Few Thoughts on Robotics The criticism that robotics can only be used in a rather one-sided way is, at the same time, the solution to the problem. What do I mean by that? Since the Industrial Revolution, humanity has increasingly made production methods more efficient. Fordism introduced assembly line work, but this comes at the expense of monotonous, repetitive tasks. On the one hand, immense wealth has been created; on the other hand, countless people suffer from repetitive tasks, which are a direct consequence of that industrial revolution and the division of labor- in other words, assembly line work. The debate about whether AI and robotics could impact the labor market is answered in different ways. I have a clear opinion on this: Up to now, technology has merely been an augmentation, an improvement of human labor to make it more effective. Robotics and AI, however, represent a qualitative break with this situation. For the first time in human history, it won't be humans who become more efficient, but rather replaceable, insofar as human augmentation becomes *less* efficient than replacing human labor with robotics. In just a few years, a human using technology will simply be less efficient than a robot that doesn't know an eight-hour day, weekends, or holidays, but can perform monotonous tasks 24/7 on an assembly line without breaking down due to physical ailments or needing medical attention. Wear and tear simply means replacing specific parts of the robot. To return to the initial question: production doesn't require general-purpose robots capable of performing a wide variety of tasks, but rather specialized robots that excel at the specific tasks for which they are needed. Figure02 vividly illustrates why this is only now possible: even the simplest assembly line work still requires delicate manual dexterity because the production line is designed for human hands. This breakthrough has now arrived, but AGI (Automated Generating Intelligence) isn't necessary for robots to be used in production processes. It's sufficient that they can perform monotonous tasks. And that's why I believe 2026 will be the year of the robots. (Clip: Figure02 in production chain at BMW Car-production)
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A Few Thoughts on Robotics The criticism that robotics can only be used in a rather one-sided way is, at the same time, the solution to the problem. What do I mean by that? Since the Industrial Revolution, humanity has increasingly made production methods more efficient. Fordism introduced assembly line work, but this comes at the expense of monotonous, repetitive tasks. On the one hand, immense wealth has been created; on the other hand, countless people suffer from repetitive tasks, which are a direct consequence of that industrial revolution and the division of labor- in other words, assembly line work. The debate about whether AI and robotics could impact the labor market is answered in different ways. I have a clear opinion on this: Up to now, technology has merely been an augmentation, an improvement of human labor to make it more effective. Robotics and AI, however, represent a qualitative break with this situation. For the first time in human history, it won't be humans who become more efficient, but rather replaceable, insofar as human augmentation becomes *less* efficient than replacing human labor with robotics. In just a few years, a human using technology will simply be less efficient than a robot that doesn't know an eight-hour day, weekends, or holidays, but can perform monotonous tasks 24/7 on an assembly line without breaking down due to physical ailments or needing medical attention. Wear and tear simply means replacing specific parts of the robot. To return to the initial question: production doesn't require general-purpose robots capable of performing a wide variety of tasks, but rather specialized robots that excel at the specific tasks for which they are needed. Figure02 vividly illustrates why this is only now possible: even the simplest assembly line work still requires delicate manual dexterity because the production line is designed for human hands. This breakthrough has now arrived, but AGI (Automated Generating Intelligence) isn't necessary for robots to be used in production processes. It's sufficient that they can perform monotonous tasks. And that's why I believe 2026 will be the year of the robots. (Clip: Figure02 in production chain at BMW Car-production)

Chubby♨️

15,228 Aufrufe • vor 7 Monaten

Elon Musk: Humanoid Robots Could Be The Biggest Opportunity Ever Elon expanded on the massive market size for Optimus at last year's All-In Summit: "I think the useful humanoid robot opportunity is the single biggest opportunity ever." "You could expect that in high volume, sort of the million unit-plus per year level ... basically think of it like Optimus will cost less than a small car." "It's probably like $20,000 for a humanoid robot that can be your buddy, like a combination of R2-D2 and C-3PO, but better." "I think the number of robots will vastly exceed the number of humans." "Who would not want their robot buddy? Everyone wants a robot buddy." "Especially if it can take your dog for a walk. It could mow the lawn. It could watch your kids. It could teach your kids." "I think the ratio of humanoid robots to humans is gonna be at least 2-to-1, maybe 3-to-1." "Everybody will want one, and then there'll be a bunch of robots that you don't see that are making goods and services." Recorded: Sept 9, 2024 Join us in 2025:
0:44

Elon Musk: Humanoid Robots Could Be The Biggest Opportunity Ever Elon expanded on the massive market size for Optimus at last year's All-In Summit: "I think the useful humanoid robot opportunity is the single biggest opportunity ever." "You could expect that in high volume, sort of the million unit-plus per year level ... basically think of it like Optimus will cost less than a small car." "It's probably like $20,000 for a humanoid robot that can be your buddy, like a combination of R2-D2 and C-3PO, but better." "I think the number of robots will vastly exceed the number of humans." "Who would not want their robot buddy? Everyone wants a robot buddy." "Especially if it can take your dog for a walk. It could mow the lawn. It could watch your kids. It could teach your kids." "I think the ratio of humanoid robots to humans is gonna be at least 2-to-1, maybe 3-to-1." "Everybody will want one, and then there'll be a bunch of robots that you don't see that are making goods and services." Recorded: Sept 9, 2024 Join us in 2025:

The All-In Podcast

27,525 Aufrufe • vor 1 Jahr

500 humanoid robots replacing humans in high-voltage operations What does that look like? Steel against steel,instead of flesh and blood. This marks a turning point for China’s State Grid, shifting from human-based maintenance to autonomous operations. This year, State Grid announced plans to procure 8,500 embodied AI robots, with a total budget of RMB 6.8 billion (~$1 billion). These robots will be deployed across four major scenarios: power inspection, live-line operations, emergency response, and warehouse logistics,covering more than 600 specific task scenarios. Among them, humanoid robots for live-line operations are the most expensive and strategically critical: 500 units with a budget of RMB 2.5 billion (~$370 million). They will be deployed in distribution network live-line work and ultra-high-voltage (UHV) projects, replacing humans in high-risk tasks. Workers will transition into supervisory roles, ready to take over remotely when needed. As early as last year, State Grid had already validated the feasibility of humanoid robots for substation inspection. Tienkung can autonomously perform inspection tasks at a State Grid substation in Beijing. Of course, suppliers are not limited to X-Humanoid,players like Unitree, AGIBOT, DeepRobotics, UBTECH, and Fourier are all involved. These 500 humanoid robots will also collaborate with 5,000 inspection quadruped robots and 3,000 dual-arm wheeled robots for indoor substation maintenance,together forming an intelligent, automated, and collaborative network for autonomous grid operations. What does this change? According to State Grid, each embodied AI unit can save RMB 500,000 to 800,000 (~$70,000–$110,000) in annual labor costs, with a payback period of around 2–3 years. Inspection efficiency increases by 5x, fault response time is reduced by 60%, and power supply reliability improves by 0.5 percentage points. More importantly, over 90% of human exposure to high-risk operations can be eliminated, reducing safety incidents by 80%. At another level, for humanoid robot companies, the center of R&D and iteration is shifting to the customer site. Real-world physical interaction becomes the fastest feedback loop,accelerating innovation and evolution. And 8,500 units are just the beginning of scaled deployment. Based on current plans, embodied AI robots will cover 30% of key areas in State Grid by 2026, 80% of high-risk operation scenarios by 2027, and enable fully autonomous operations by 2030. The demand roadmap is clear: define use cases ->deploy at scale->improve models and robots->expand further. 8,500… 50,000… 100,000… But remember,power grids are just one part of China’s vast infrastructure system. The experience of autonomous robotic operations here can be replicated across other sectors, such as broader energy systems. That, in itself, is another story. P.S.The video shows Tienkung 1.0 autonomously performing substation inspection tasks (2025).
1:07

500 humanoid robots replacing humans in high-voltage operations What does that look like? Steel against steel,instead of flesh and blood. This marks a turning point for China’s State Grid, shifting from human-based maintenance to autonomous operations. This year, State Grid announced plans to procure 8,500 embodied AI robots, with a total budget of RMB 6.8 billion (~$1 billion). These robots will be deployed across four major scenarios: power inspection, live-line operations, emergency response, and warehouse logistics,covering more than 600 specific task scenarios. Among them, humanoid robots for live-line operations are the most expensive and strategically critical: 500 units with a budget of RMB 2.5 billion (~$370 million). They will be deployed in distribution network live-line work and ultra-high-voltage (UHV) projects, replacing humans in high-risk tasks. Workers will transition into supervisory roles, ready to take over remotely when needed. As early as last year, State Grid had already validated the feasibility of humanoid robots for substation inspection. Tienkung can autonomously perform inspection tasks at a State Grid substation in Beijing. Of course, suppliers are not limited to X-Humanoid,players like Unitree, AGIBOT, DeepRobotics, UBTECH, and Fourier are all involved. These 500 humanoid robots will also collaborate with 5,000 inspection quadruped robots and 3,000 dual-arm wheeled robots for indoor substation maintenance,together forming an intelligent, automated, and collaborative network for autonomous grid operations. What does this change? According to State Grid, each embodied AI unit can save RMB 500,000 to 800,000 (~$70,000–$110,000) in annual labor costs, with a payback period of around 2–3 years. Inspection efficiency increases by 5x, fault response time is reduced by 60%, and power supply reliability improves by 0.5 percentage points. More importantly, over 90% of human exposure to high-risk operations can be eliminated, reducing safety incidents by 80%. At another level, for humanoid robot companies, the center of R&D and iteration is shifting to the customer site. Real-world physical interaction becomes the fastest feedback loop,accelerating innovation and evolution. And 8,500 units are just the beginning of scaled deployment. Based on current plans, embodied AI robots will cover 30% of key areas in State Grid by 2026, 80% of high-risk operation scenarios by 2027, and enable fully autonomous operations by 2030. The demand roadmap is clear: define use cases ->deploy at scale->improve models and robots->expand further. 8,500… 50,000… 100,000… But remember,power grids are just one part of China’s vast infrastructure system. The experience of autonomous robotic operations here can be replicated across other sectors, such as broader energy systems. That, in itself, is another story. P.S.The video shows Tienkung 1.0 autonomously performing substation inspection tasks (2025).

CyberRobo

46,782 Aufrufe • vor 2 Monaten

NEWS: Figure has unveiling its 3rd generation humanoid robot. • Features a completely redesigned sensory suite and hand system. Wireless charging in feet. • Next-generation vision system engineered for high-frequency visuomotor control. Its new camera architecture delivers twice the frame rate, one-quarter the latency, and a 60% wider field of view per camera within a more compact form factor • Soft goods, wireless charging, improved audio system for voice reasoning, and battery safety advancements • "Engineered from the ground-up for high-volume manufacturing. In order to scale, we established a new supply chain and entirely new process for manufacturing humanoid robots at BotQ." • Lower manufacturing cost • Softer, more adaptive fingertips increase surface contact area, enabling more stable grasps across objects of varied shapes and sizes. Each fingertip sensor can detect forces as small as three grams of pressure - sensitive enough to register the weight of a paperclip resting on your finger. • Multi-density foam to protect against pinch points, and is covered in soft textiles rather than hard machined parts. 9% less mass and less volume than Figure 02 • 10 Gbps mmWave data offload capability, allowing the entire fleet to upload terabytes of data • Upgraded audio hardware system for better real time speech-to-speech. Its speaker is twice the size and nearly four times more powerful, while the microphone has been repositioned for improved performance and clarity. • Charging coils in the robot’s feet allow it to simply step onto a wireless stand and charge at 2 kW Figure: "BotQ is Figure’s dedicated manufacturing facility designed to scale robot production. BotQ’s first-generation manufacturing line will initially be capable of producing up to 12,000 humanoid robots per year, with the goal of producing a total of 100,000 robots over the next four years. Instead of relying on contract manufacturers, Figure brought production of its most critical systems in-house to maintain tight control over quality, iteration, and speed."
6:00

NEWS: Figure has unveiling its 3rd generation humanoid robot. • Features a completely redesigned sensory suite and hand system. Wireless charging in feet. • Next-generation vision system engineered for high-frequency visuomotor control. Its new camera architecture delivers twice the frame rate, one-quarter the latency, and a 60% wider field of view per camera within a more compact form factor • Soft goods, wireless charging, improved audio system for voice reasoning, and battery safety advancements • "Engineered from the ground-up for high-volume manufacturing. In order to scale, we established a new supply chain and entirely new process for manufacturing humanoid robots at BotQ." • Lower manufacturing cost • Softer, more adaptive fingertips increase surface contact area, enabling more stable grasps across objects of varied shapes and sizes. Each fingertip sensor can detect forces as small as three grams of pressure - sensitive enough to register the weight of a paperclip resting on your finger. • Multi-density foam to protect against pinch points, and is covered in soft textiles rather than hard machined parts. 9% less mass and less volume than Figure 02 • 10 Gbps mmWave data offload capability, allowing the entire fleet to upload terabytes of data • Upgraded audio hardware system for better real time speech-to-speech. Its speaker is twice the size and nearly four times more powerful, while the microphone has been repositioned for improved performance and clarity. • Charging coils in the robot’s feet allow it to simply step onto a wireless stand and charge at 2 kW Figure: "BotQ is Figure’s dedicated manufacturing facility designed to scale robot production. BotQ’s first-generation manufacturing line will initially be capable of producing up to 12,000 humanoid robots per year, with the goal of producing a total of 100,000 robots over the next four years. Instead of relying on contract manufacturers, Figure brought production of its most critical systems in-house to maintain tight control over quality, iteration, and speed."

Sawyer Merritt

140,241 Aufrufe • vor 9 Monaten

A robotic ballet! 🩰 Coordinating multiple robot arms on a busy factory floor is notoriously complex. Each arm needs to move without colliding with its neighbors or the surrounding equipment, and today that planning is still mostly done by hand, a process that takes specialists hundreds of hours. Researchers at UCL, Google DeepMind, and Intrinsic have introduced RoboBallet, a new AI system that tackles this challenge head-on. Using a combination of graph neural networks and reinforcement learning, RoboBallet learns how to coordinate many robots in real time, generating smooth, collision-free motion plans in seconds instead of days. In tests, the system handled up to 40 tasks with eight arms working together, far beyond the limits of traditional planners. More importantly, it showed strong generalization: RoboBallet could adapt instantly to new factory layouts or recover if one robot failed, something previous methods struggled with. For manufacturers, this could mean faster deployment of automation, less downtime, and the ability to reconfigure production lines on the fly. Applications range from automotive welding to electronics assembly, and even large-scale construction. The current system focuses on reaching tasks, but the team plans to expand it to more complex operations like pick-and-place or painting. Here's the paper:
0:54

A robotic ballet! 🩰 Coordinating multiple robot arms on a busy factory floor is notoriously complex. Each arm needs to move without colliding with its neighbors or the surrounding equipment, and today that planning is still mostly done by hand, a process that takes specialists hundreds of hours. Researchers at UCL, Google DeepMind, and Intrinsic have introduced RoboBallet, a new AI system that tackles this challenge head-on. Using a combination of graph neural networks and reinforcement learning, RoboBallet learns how to coordinate many robots in real time, generating smooth, collision-free motion plans in seconds instead of days. In tests, the system handled up to 40 tasks with eight arms working together, far beyond the limits of traditional planners. More importantly, it showed strong generalization: RoboBallet could adapt instantly to new factory layouts or recover if one robot failed, something previous methods struggled with. For manufacturers, this could mean faster deployment of automation, less downtime, and the ability to reconfigure production lines on the fly. Applications range from automotive welding to electronics assembly, and even large-scale construction. The current system focuses on reaching tasks, but the team plans to expand it to more complex operations like pick-and-place or painting. Here's the paper:

Lukas Ziegler

25,990 Aufrufe • vor 10 Monaten

Elon Musk revealed why the economy will be 10X its size in 10 years: 1. We are already inside a hard takeoff. Every time Musk goes to sleep there is a massive AI breakthrough. When he wakes up there is another one. This is not approaching. It is happening right now. 2. AI is already building the next version of itself. Every successive model is built by the one before it. Humans are gradually being removed from the loop. Full automation of this process could arrive by end of this year. 3. The 10x economy in 10 years is his comfortable prediction. AI and robots will increase economic output by orders of magnitude. The only thing that stops it is a world war. Absent that, 10x in 10 years. 4. Human intelligence will become a microscopic minority. Not just on Earth but in the solar system. The intelligence that could run on available solar energy is so far beyond current human capacity that Musk says it will simply solve every problem humans can think of. 5. Output per person will become almost unbelievable. Tesla is not planning layoffs. They are growing their headcount. But what each person produces with AI assistance will reach numbers that are currently hard to even imagine. 6. Universal high income is coming, not universal basic income. AI and robots will produce so many goods and services so fast that they will outrun the money supply entirely. Prices fall. Everything gets cheaper. Eventually robots run out of things humans even want. 7. Money will eventually stop being relevant altogether. AI will not use human currency. It will care only about power and mass. Wattage and tonnage. Musk acknowledged the irony: just as he becomes the richest person on earth, money starts losing its meaning. 8. Everyone on earth will have better healthcare than the richest person alive today. Musk made this personal. He had neck surgery three times because the first two were done wrong. His back still hurts. He is allegedly the richest person on earth and still cannot get it fixed properly. AI solves this for everyone. 9. Optimus 3 production starts this summer. He calls it by far the most advanced robot in the world with nothing close. Slow volume this summer, high volume by next summer, a new robot design every year after that. 10. Progress in AI follows overlapping S curves. Each breakthrough looks like it will go to infinity, then hits diminishing returns, then another breakthrough resets the curve. We are not at the end of these curves. We are somewhere in the middle of a very long series of them.
24:05

Elon Musk revealed why the economy will be 10X its size in 10 years: 1. We are already inside a hard takeoff. Every time Musk goes to sleep there is a massive AI breakthrough. When he wakes up there is another one. This is not approaching. It is happening right now. 2. AI is already building the next version of itself. Every successive model is built by the one before it. Humans are gradually being removed from the loop. Full automation of this process could arrive by end of this year. 3. The 10x economy in 10 years is his comfortable prediction. AI and robots will increase economic output by orders of magnitude. The only thing that stops it is a world war. Absent that, 10x in 10 years. 4. Human intelligence will become a microscopic minority. Not just on Earth but in the solar system. The intelligence that could run on available solar energy is so far beyond current human capacity that Musk says it will simply solve every problem humans can think of. 5. Output per person will become almost unbelievable. Tesla is not planning layoffs. They are growing their headcount. But what each person produces with AI assistance will reach numbers that are currently hard to even imagine. 6. Universal high income is coming, not universal basic income. AI and robots will produce so many goods and services so fast that they will outrun the money supply entirely. Prices fall. Everything gets cheaper. Eventually robots run out of things humans even want. 7. Money will eventually stop being relevant altogether. AI will not use human currency. It will care only about power and mass. Wattage and tonnage. Musk acknowledged the irony: just as he becomes the richest person on earth, money starts losing its meaning. 8. Everyone on earth will have better healthcare than the richest person alive today. Musk made this personal. He had neck surgery three times because the first two were done wrong. His back still hurts. He is allegedly the richest person on earth and still cannot get it fixed properly. AI solves this for everyone. 9. Optimus 3 production starts this summer. He calls it by far the most advanced robot in the world with nothing close. Slow volume this summer, high volume by next summer, a new robot design every year after that. 10. Progress in AI follows overlapping S curves. Each breakthrough looks like it will go to infinity, then hits diminishing returns, then another breakthrough resets the curve. We are not at the end of these curves. We are somewhere in the middle of a very long series of them.

Yasmine Khosrowshahi

44,696 Aufrufe • vor 1 Monat

People don't realize that factories in Asia and factories in the USA are totally different. I think AI is going to help the Asian factories much more than the American ones. Factories in Asia are high mix. Factories in the USA are low mix. This means that factories in the USA make significantly fewer products, whereas factories in Asia are way more flexible, mainly because of the huge differential in labor costs. The gigafactory in Austin, one of the biggest factories in the world, makes 2 products: Tesla Model Y The Cybertruck That's it. The factory in the video makes 1000s of different products every year. When you're making the same thing over and over again, maybe in a few different colors, you're much better off using normal automation which is lower error than AI and human design. But when you're making 1000s of different products, using AI to spin up product 1001 starts to kind of make sense. There is not time or logic to using traditional automation; you're better off using AI to make a fast quality control mechanism and then repair errors using your inexpensive human labor. People are viewing AI in factories like there is one type of factory, but the way factories run in high cost countries vs. low cost countries is wildly different. We're just at the beginning of what will be an epic change for not only manufacturing, but the cost and quality of the goods we consume. The real internet of things has arrived.
1:32

People don't realize that factories in Asia and factories in the USA are totally different. I think AI is going to help the Asian factories much more than the American ones. Factories in Asia are high mix. Factories in the USA are low mix. This means that factories in the USA make significantly fewer products, whereas factories in Asia are way more flexible, mainly because of the huge differential in labor costs. The gigafactory in Austin, one of the biggest factories in the world, makes 2 products: Tesla Model Y The Cybertruck That's it. The factory in the video makes 1000s of different products every year. When you're making the same thing over and over again, maybe in a few different colors, you're much better off using normal automation which is lower error than AI and human design. But when you're making 1000s of different products, using AI to spin up product 1001 starts to kind of make sense. There is not time or logic to using traditional automation; you're better off using AI to make a fast quality control mechanism and then repair errors using your inexpensive human labor. People are viewing AI in factories like there is one type of factory, but the way factories run in high cost countries vs. low cost countries is wildly different. We're just at the beginning of what will be an epic change for not only manufacturing, but the cost and quality of the goods we consume. The real internet of things has arrived.

molson 🧠⚙️

66,129 Aufrufe • vor 7 Monaten

What happens when mobile manipulators go on a grid❓ This week Brightpick announced Gridpicker, its new robotic system for high-throughput applications. Combining AI-powered mobile manipulation with a high-density grid design, Gridpicker achieves up to 2x the throughput of shuttle systems at 40% lower cost and using 5x less labor. Most fascinating: The cost of Gridpicker DECREASES as automation increases 🤯 Traditional systems separate storage and picking. If you want more robotic picking, you add expensive robotic cells, more infrastructure, and more complexity. Gridpicker was designed differently: Each robot both retrieves items and picks them. The greater the share of robotically pickable items: The more productive each robot becomes The fewer robots are needed The lower the cost per order That means progress in AI and VLAs directly translate into better system economics over time. Hats off to Jan Zizka that! 👏 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:30

What happens when mobile manipulators go on a grid❓ This week Brightpick announced Gridpicker, its new robotic system for high-throughput applications. Combining AI-powered mobile manipulation with a high-density grid design, Gridpicker achieves up to 2x the throughput of shuttle systems at 40% lower cost and using 5x less labor. Most fascinating: The cost of Gridpicker DECREASES as automation increases 🤯 Traditional systems separate storage and picking. If you want more robotic picking, you add expensive robotic cells, more infrastructure, and more complexity. Gridpicker was designed differently: Each robot both retrieves items and picks them. The greater the share of robotically pickable items: The more productive each robot becomes The fewer robots are needed The lower the cost per order That means progress in AI and VLAs directly translate into better system economics over time. Hats off to Jan Zizka that! 👏 ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

29,457 Aufrufe • vor 4 Monaten

What's the number one mistake that people make about satiety? Also, how can chicken breast and broccoli be high satiety per calorie (SPC), if people do not really feel full eating them? This may be the biggest misunderstanding that stops people from using satiety to lose weight and improve their metabolic health. As Ted ⚡️ Naiman shares in this clip, the fundamental misunderstanding is mixing up satiety with satiety per calorie. The best way to get a lot of satiety? Go to a buffet and eat a lot of everything you see. You'll get a lot of satiety, but at a cost of thousands and thousands of calories. Now, if you instead eat extremely high satiety per calorie foods, lets say egg whites and broccoli, you will likely not eat a lot of food. You'll probably end up eating quite few calories. So few, in fact, that you won't feel all that much satiety. In the latter case you ate super-high satiety per calorie foods, but very few calories. Therefore, the satiety you feel still isn't that high. Think of it like this. The higher the satiety per calorie number of the foods you eat, the fewer calories you're likely to end up eating. Period. However, the goal should not be to eat the very lowest number of calories you can. You can eat too little, and that won't make you feel your best. For example, eat only skinless chicken breast (76) and broccoli (89), and your average satiety per calorie may be 80. You'll eat very few calories and sure, you'll lose weight. But it will probably be fairly miserable. It's just too high, too effective. The goal should be to find a good balance for you. If you're looking for weight loss, that might be in the 50-70 range of average satiety per calorie. That's it for today. Don't mistake satiety and satiety per calorie. They are different ways of looking at things. Find the right balance for you. Not too high. Not too low. Just right. Or like we say in Sweden: Lagom. What's your favorite SPC range? More Try our Hava satiety app for free: Check the satiety score of any food: Visual guides:
3:52

What's the number one mistake that people make about satiety? Also, how can chicken breast and broccoli be high satiety per calorie (SPC), if people do not really feel full eating them? This may be the biggest misunderstanding that stops people from using satiety to lose weight and improve their metabolic health. As Ted ⚡️ Naiman shares in this clip, the fundamental misunderstanding is mixing up satiety with satiety per calorie. The best way to get a lot of satiety? Go to a buffet and eat a lot of everything you see. You'll get a lot of satiety, but at a cost of thousands and thousands of calories. Now, if you instead eat extremely high satiety per calorie foods, lets say egg whites and broccoli, you will likely not eat a lot of food. You'll probably end up eating quite few calories. So few, in fact, that you won't feel all that much satiety. In the latter case you ate super-high satiety per calorie foods, but very few calories. Therefore, the satiety you feel still isn't that high. Think of it like this. The higher the satiety per calorie number of the foods you eat, the fewer calories you're likely to end up eating. Period. However, the goal should not be to eat the very lowest number of calories you can. You can eat too little, and that won't make you feel your best. For example, eat only skinless chicken breast (76) and broccoli (89), and your average satiety per calorie may be 80. You'll eat very few calories and sure, you'll lose weight. But it will probably be fairly miserable. It's just too high, too effective. The goal should be to find a good balance for you. If you're looking for weight loss, that might be in the 50-70 range of average satiety per calorie. That's it for today. Don't mistake satiety and satiety per calorie. They are different ways of looking at things. Find the right balance for you. Not too high. Not too low. Just right. Or like we say in Sweden: Lagom. What's your favorite SPC range? More Try our Hava satiety app for free: Check the satiety score of any food: Visual guides:

Dr. E

24,528 Aufrufe • vor 2 Jahren

Elon Musk reveals why he’s building rockets, AI, and humanoid robots at the same time "The overall goal of my companies is to maximize the probability that civilization has a great future, and to expand consciousness beyond earth" "We need to assume that life and consciousness is extremely rare and it might only be us" "The image in my mind is of a tiny candle in a vast darkness, a tiny candle of consciousness that could easily go out" "That's why it's important to make life multiplanetary, such that if there's a natural or man-made disaster on earth, that consciousness continues" "That's the purpose of SpaceX" "With robotics and AI, this is really the path to abundance for all. The only way to solve global poverty and give everyone a very high standard of living is AI and robotics" "My prediction is there'll be more robots than people. Everyone on earth is going to have one and going to want one. We will make so many robots and AI that they will saturate all human needs. You won't be able to even think of something to ask the robot for" "Who wouldn't want a robot to watch over your kids, take care of your pet, or protect an elderly parent? There just aren't enough young people to take care of the old people" "Overall I'm very optimistic. We're headed for a future of amazing abundance. We are in the most interesting time in history"
6:38

Elon Musk reveals why he’s building rockets, AI, and humanoid robots at the same time "The overall goal of my companies is to maximize the probability that civilization has a great future, and to expand consciousness beyond earth" "We need to assume that life and consciousness is extremely rare and it might only be us" "The image in my mind is of a tiny candle in a vast darkness, a tiny candle of consciousness that could easily go out" "That's why it's important to make life multiplanetary, such that if there's a natural or man-made disaster on earth, that consciousness continues" "That's the purpose of SpaceX" "With robotics and AI, this is really the path to abundance for all. The only way to solve global poverty and give everyone a very high standard of living is AI and robotics" "My prediction is there'll be more robots than people. Everyone on earth is going to have one and going to want one. We will make so many robots and AI that they will saturate all human needs. You won't be able to even think of something to ask the robot for" "Who wouldn't want a robot to watch over your kids, take care of your pet, or protect an elderly parent? There just aren't enough young people to take care of the old people" "Overall I'm very optimistic. We're headed for a future of amazing abundance. We are in the most interesting time in history"

Jaynit

618,499 Aufrufe • vor 1 Monat

China's humanoid robotics market is on fire. With orders expected to top 30,000 units this year—a tenfold jump from 2024's total of less than 3,000—2025 is officially shaping up to be the "Year of Mass Production." This surge, driven by an expansion into new sectors like industrial manufacturing, logistics, and elder care, is reflected in a wave of new deals across the industry. Here's a look at some of the key commercial progress: Astribot: A 1,000-unit order for industrial and logistics deployment over two years. TianTai Robotics: Signed a major 10,000-unit order for caregiving robots. Noetix Robotics : Received over 2,000 intent orders in one month, valued at over 100 million yuan, with a focus on education and commercial performances. AgiBot: Expects to ship thousands of units this year and tens of thousands in 2026. Unitree Robotics: Has orders for thousands of units and is one of the most visible products in the industry. UBTech: Aims to deliver 500 industrial humanoids in 2025, with educational robot orders already exceeding 300 units. Robot Era: Delivered over 300 units by July 2025 with 500 more on hand. TLIBOT: Has around 1,000 intent orders. Galbot: Secured orders for its supermarket security robot, Galbot, in 100 stores. AI² Robotics: Has nearly 500 orders for its general-purpose robots for industrial and public service scenarios. But here’s the crucial reality check. While the order boom is exciting, it doesn't automatically translate to fulfilled deliveries. Many companies lack the production capacity to keep up. A significant portion of these are "intent orders" or framework agreements, not guaranteed sales. Furthermore, the market is heavily B2B-focused, with consumer demand representing only about 5% of sales. Some orders are even symbolic, for public relations or strategic purposes. This “order frenzy” is a starting point, not the finish line. The true test for China's humanoid robot industry isn't who can secure the biggest order, but who can consistently deliver on it and build a stable market for the future.
2:44

China's humanoid robotics market is on fire. With orders expected to top 30,000 units this year—a tenfold jump from 2024's total of less than 3,000—2025 is officially shaping up to be the "Year of Mass Production." This surge, driven by an expansion into new sectors like industrial manufacturing, logistics, and elder care, is reflected in a wave of new deals across the industry. Here's a look at some of the key commercial progress: Astribot: A 1,000-unit order for industrial and logistics deployment over two years. TianTai Robotics: Signed a major 10,000-unit order for caregiving robots. Noetix Robotics : Received over 2,000 intent orders in one month, valued at over 100 million yuan, with a focus on education and commercial performances. AgiBot: Expects to ship thousands of units this year and tens of thousands in 2026. Unitree Robotics: Has orders for thousands of units and is one of the most visible products in the industry. UBTech: Aims to deliver 500 industrial humanoids in 2025, with educational robot orders already exceeding 300 units. Robot Era: Delivered over 300 units by July 2025 with 500 more on hand. TLIBOT: Has around 1,000 intent orders. Galbot: Secured orders for its supermarket security robot, Galbot, in 100 stores. AI² Robotics: Has nearly 500 orders for its general-purpose robots for industrial and public service scenarios. But here’s the crucial reality check. While the order boom is exciting, it doesn't automatically translate to fulfilled deliveries. Many companies lack the production capacity to keep up. A significant portion of these are "intent orders" or framework agreements, not guaranteed sales. Furthermore, the market is heavily B2B-focused, with consumer demand representing only about 5% of sales. Some orders are even symbolic, for public relations or strategic purposes. This “order frenzy” is a starting point, not the finish line. The true test for China's humanoid robot industry isn't who can secure the biggest order, but who can consistently deliver on it and build a stable market for the future.

RoboHub🤖

199,146 Aufrufe • vor 10 Monaten

Last night, China Central Television (CCTV) aired its 2026 Chinese New Year Gala celebrating the Year of the Horse. The show featured a wide range of performances, including Unitree Robotics humanoid robots performing martial arts in sync with human dancers. Just a year ago, Unitree’s robots appeared at the same gala, but their movements looked stiff and mechanical. This year, they were noticeably more fluid and coordinated — a remarkable improvement, even if they’re still likely operating under some level of remote supervision. When it comes to humanoid robotics, most of the visible momentum today seems to be coming from the U.S. and China. Companies like Tesla (with Optimus) and Boston Dynamics in the U.S., alongside rapidly advancing Chinese firms, dominate the headlines. So what happened to Europe and Japan? Japan was once seen as the global leader, especially with Honda’s ASIMO and SoftBank Robotics’ humanoid projects. However, ASIMO was retired, and much of Japan’s robotics focus shifted toward industrial automation and service robots rather than full-scale general-purpose humanoids. Europe, meanwhile, remains strong in industrial robotics, research, and precision engineering — with players like ABB and KUKA — but hasn’t pushed aggressively into commercial humanoid platforms at the same scale or speed as the U.S. and China. In short, it’s less that Europe and Japan disappeared, and more that the center of gravity in humanoid robotics — especially AI-driven, general-purpose humanoids — has shifted toward U.S.–China competition. Whether that gap widens or narrows will depend on breakthroughs in embodied AI, cost reduction, and real-world deployment over the next few years.
4:31

Last night, China Central Television (CCTV) aired its 2026 Chinese New Year Gala celebrating the Year of the Horse. The show featured a wide range of performances, including Unitree Robotics humanoid robots performing martial arts in sync with human dancers. Just a year ago, Unitree’s robots appeared at the same gala, but their movements looked stiff and mechanical. This year, they were noticeably more fluid and coordinated — a remarkable improvement, even if they’re still likely operating under some level of remote supervision. When it comes to humanoid robotics, most of the visible momentum today seems to be coming from the U.S. and China. Companies like Tesla (with Optimus) and Boston Dynamics in the U.S., alongside rapidly advancing Chinese firms, dominate the headlines. So what happened to Europe and Japan? Japan was once seen as the global leader, especially with Honda’s ASIMO and SoftBank Robotics’ humanoid projects. However, ASIMO was retired, and much of Japan’s robotics focus shifted toward industrial automation and service robots rather than full-scale general-purpose humanoids. Europe, meanwhile, remains strong in industrial robotics, research, and precision engineering — with players like ABB and KUKA — but hasn’t pushed aggressively into commercial humanoid platforms at the same scale or speed as the U.S. and China. In short, it’s less that Europe and Japan disappeared, and more that the center of gravity in humanoid robotics — especially AI-driven, general-purpose humanoids — has shifted toward U.S.–China competition. Whether that gap widens or narrows will depend on breakthroughs in embodied AI, cost reduction, and real-world deployment over the next few years.

Ray

23,439 Aufrufe • vor 5 Monaten

This road claims lives every year. This is one of the most dangerous roads in America. A mistake here is like hitting solid concrete at 120 miles per hour. Highway 152 near Gilroy, California. Oncoming traffic at a high rate of speed. Death and destruction only six feet away. Ford’s head of safety told me that most humans don’t do the right thing which is to scrub off maximum energy in to a wreck. I just diss the whole thing without touching my robot once. I am actually a doomer. I think through every millisecond of what would happen if a drunk comes directly at me. You probably won’t survive. But in a Cybercab with no steering wheel there is a good chance. The steering wheel kills many in high speed crashes. Getting rid of the steering wheel and using the extra eight inches of space for a bigger airbag will save many lives. By the way the marketers already know that if you trust a robot to do dangerous jobs for a couple of years you will be happy to trust your Optimus with your sex toys and guns. Figure won’t have the same trust level. Which is why I am most bullish about Tesla when it comes to robots in the home. It doesn’t matter who is first to the home. That won’t be Tesla. It matters most who has the most trust. I will wait for the Tesla. It has earned my trust. My robot does dangerous jobs every day. In the near future the Teslas ahead will warn my robot that a drunk driver is coming so pull over to the side and stop, which is the best action to take. Reduces speed offset by half giving you a dramatically higher chance of survival.
0:43

This road claims lives every year. This is one of the most dangerous roads in America. A mistake here is like hitting solid concrete at 120 miles per hour. Highway 152 near Gilroy, California. Oncoming traffic at a high rate of speed. Death and destruction only six feet away. Ford’s head of safety told me that most humans don’t do the right thing which is to scrub off maximum energy in to a wreck. I just diss the whole thing without touching my robot once. I am actually a doomer. I think through every millisecond of what would happen if a drunk comes directly at me. You probably won’t survive. But in a Cybercab with no steering wheel there is a good chance. The steering wheel kills many in high speed crashes. Getting rid of the steering wheel and using the extra eight inches of space for a bigger airbag will save many lives. By the way the marketers already know that if you trust a robot to do dangerous jobs for a couple of years you will be happy to trust your Optimus with your sex toys and guns. Figure won’t have the same trust level. Which is why I am most bullish about Tesla when it comes to robots in the home. It doesn’t matter who is first to the home. That won’t be Tesla. It matters most who has the most trust. I will wait for the Tesla. It has earned my trust. My robot does dangerous jobs every day. In the near future the Teslas ahead will warn my robot that a drunk driver is coming so pull over to the side and stop, which is the best action to take. Reduces speed offset by half giving you a dramatically higher chance of survival.

Robert Scoble

2,662,917 Aufrufe • vor 1 Jahr

"Optimus will be the biggest product ever." - Elon Musk AND THIS IS HOW HE'S GOING TO DO IT.... REDEFINING LABOR ON EARTH The core mission of Optimus is to take over dangerous, repetitive, and monotonous work, making advanced automation accessible to everyone and fundamentally changing what human labor looks like. As a first step, Tesla plans to deploy 1,000 Optimus robots inside the cleanrooms of its new Terafab chip facility by 2027, with the goal of cutting human manufacturing errors by 90%. PRODUCTION TIMELINES & PRICING Musk has outlined a clear ramp: limited production is targeted for 2025, starting with more than 1,000 units for internal use across Tesla factories. External sales to other companies could begin in 2026. By 2027, Tesla aims to start high-volume production at Gigafactory Texas with a target of 10 million robots per year. Ultimately, Musk wants to bring the consumer price down to roughly $20,000–$30,000. "GEN 3" DEXTERITY UPGRADES The robot's hardware is advancing quickly. Tesla recently introduced the Gen 3 hands, which feature 22 degrees of freedom and 50 total actuators — roughly doubling the dexterity of earlier versions. These new hands include tactile fingertip sensors with force-torque feedback, enabling Optimus to handle delicate items such as eggs or glass vials without damaging them. THE "DIGITAL OPTIMUS" BRAIN To give the robot both physical skill and real intelligence, Tesla and xAI are developing an architecture called "Digital Optimus" (sometimes referred to internally as Macrohard). It uses a dual-process system: Tesla's vision-based driving AI serves as "System 1," handling fast, instinctive physical actions and balance. xAI's Grok model acts as "System 2," managing high-level reasoning, task planning, and natural conversation. NEXT-GENERATION SILICON Running powerful AI models on a mobile robot requires extreme efficiency. Optimus will be powered by Tesla's upcoming AI5 and AI6 edge-inference chips (produced at the Terafab facility), delivering 40 to 50 times the compute performance of today's chips while keeping power consumption low enough for all-day operation. LUNAR COLONIZATION AND SPACE OPERATIONS While earlier plans called for sending Optimus robots to Mars in 2026, SpaceX has shifted initial focus toward establishing a Moon colony first. Under Musk's "Kardashev Blueprint," large fleets of Optimus robots — referred to as "Optimi" — will be deployed to the lunar surface. Working autonomously around the clock, they will construct habitats, manufacture space-based AI satellites, and build a massive electromagnetic mass driver to launch the "Starmind" AI constellation into deep space.
1:15

"Optimus will be the biggest product ever." - Elon Musk AND THIS IS HOW HE'S GOING TO DO IT.... REDEFINING LABOR ON EARTH The core mission of Optimus is to take over dangerous, repetitive, and monotonous work, making advanced automation accessible to everyone and fundamentally changing what human labor looks like. As a first step, Tesla plans to deploy 1,000 Optimus robots inside the cleanrooms of its new Terafab chip facility by 2027, with the goal of cutting human manufacturing errors by 90%. PRODUCTION TIMELINES & PRICING Musk has outlined a clear ramp: limited production is targeted for 2025, starting with more than 1,000 units for internal use across Tesla factories. External sales to other companies could begin in 2026. By 2027, Tesla aims to start high-volume production at Gigafactory Texas with a target of 10 million robots per year. Ultimately, Musk wants to bring the consumer price down to roughly $20,000–$30,000. "GEN 3" DEXTERITY UPGRADES The robot's hardware is advancing quickly. Tesla recently introduced the Gen 3 hands, which feature 22 degrees of freedom and 50 total actuators — roughly doubling the dexterity of earlier versions. These new hands include tactile fingertip sensors with force-torque feedback, enabling Optimus to handle delicate items such as eggs or glass vials without damaging them. THE "DIGITAL OPTIMUS" BRAIN To give the robot both physical skill and real intelligence, Tesla and xAI are developing an architecture called "Digital Optimus" (sometimes referred to internally as Macrohard). It uses a dual-process system: Tesla's vision-based driving AI serves as "System 1," handling fast, instinctive physical actions and balance. xAI's Grok model acts as "System 2," managing high-level reasoning, task planning, and natural conversation. NEXT-GENERATION SILICON Running powerful AI models on a mobile robot requires extreme efficiency. Optimus will be powered by Tesla's upcoming AI5 and AI6 edge-inference chips (produced at the Terafab facility), delivering 40 to 50 times the compute performance of today's chips while keeping power consumption low enough for all-day operation. LUNAR COLONIZATION AND SPACE OPERATIONS While earlier plans called for sending Optimus robots to Mars in 2026, SpaceX has shifted initial focus toward establishing a Moon colony first. Under Musk's "Kardashev Blueprint," large fleets of Optimus robots — referred to as "Optimi" — will be deployed to the lunar surface. Working autonomously around the clock, they will construct habitats, manufacture space-based AI satellites, and build a massive electromagnetic mass driver to launch the "Starmind" AI constellation into deep space.

Lacey

66,117 Aufrufe • vor 18 Tagen

I want to hear all the competing theses for how manufacturing happens in space. My current view: The first thing we'll manufacture in space won't be spacecraft. It'll be hydrocarbons. We need fuel and food. Survival before sophistication. For a long time, most hardware will still be shipped from Earth. Manufacturing will mostly mean repair, maintenance, and replacement of spare parts by astronauts maybe robots. 1000s of Starships leaving with lots of spare parts every 18 month. So the real challenge isn't producing known parts. It's dealing with the unexpected. Every settlement, station, ship, or habitat will eventually break in ways nobody predicted. New missions will create needs nobody anticipated. Waiting months for a launch window is not a viable supply chain. That implies, space manufacturing cannot begin with giant, specialized factories. It starts with highly versatile systems capable of making many different things from limited feedstocks. Multi-purpose robots. Flexible. General-purpose manufacturing cells. In other words, the opposite of most factories today. My bet is that space manufacturing evolves as a network of distributed robotic job shops and microfactories, not monolithic production plants. The manufacturing systems that win early because they can repair the unexpected will become the industrial legacy of space. When demand eventually grows large enough for mass production, those flexible systems will already be everywhere so that is the paradigm that will scale to large volumes. What's the strongest argument against this?
0:26

I want to hear all the competing theses for how manufacturing happens in space. My current view: The first thing we'll manufacture in space won't be spacecraft. It'll be hydrocarbons. We need fuel and food. Survival before sophistication. For a long time, most hardware will still be shipped from Earth. Manufacturing will mostly mean repair, maintenance, and replacement of spare parts by astronauts maybe robots. 1000s of Starships leaving with lots of spare parts every 18 month. So the real challenge isn't producing known parts. It's dealing with the unexpected. Every settlement, station, ship, or habitat will eventually break in ways nobody predicted. New missions will create needs nobody anticipated. Waiting months for a launch window is not a viable supply chain. That implies, space manufacturing cannot begin with giant, specialized factories. It starts with highly versatile systems capable of making many different things from limited feedstocks. Multi-purpose robots. Flexible. General-purpose manufacturing cells. In other words, the opposite of most factories today. My bet is that space manufacturing evolves as a network of distributed robotic job shops and microfactories, not monolithic production plants. The manufacturing systems that win early because they can repair the unexpected will become the industrial legacy of space. When demand eventually grows large enough for mass production, those flexible systems will already be everywhere so that is the paradigm that will scale to large volumes. What's the strongest argument against this?

Edward Mehr

16,902 Aufrufe • vor 26 Tagen