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Modern drone production. An assembly line in China shows how far drone manufacturing has been industrialized. Conveyor systems move the airframes between stations. Each worker performs a narrowly defined step, closer to poka-yoke than to classic workshop assembly. • Highly standardized components • Tight process segmentation • Visual quality... show more

Ilir Aliu

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139,698 次观看 • 7 个月前 •via X (Twitter)

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Insertion Verification of Ethernet Cable. It was trained and set up in minutes: This object detector and classifier can be used for robotic tasks or in assembly verification. This classifier checks whether a connector was fully inserted or not. Small automation problems like this are everywhere in manufacturing. The challenge is often not the hardware, but getting systems deployed quickly enough to create value. Credit: Lentil Robotics ——- Weekly robotics and AI insights. Subscribe free:

Insertion Verification of Ethernet Cable. It was trained and set up in minutes: This object detector and classifier can be used for robotic tasks or in assembly verification. This classifier checks whether a connector was fully inserted or not. Small automation problems like this are everywhere in manufacturing. The challenge is often not the hardware, but getting systems deployed quickly enough to create value. Credit: Lentil Robotics ——- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

26,864 次观看 • 2 个月前

A simple CNC machine. Wood. A rotating tool. And yet the pattern shifts from circles to perfect hexagons with a level of accuracy most factories still struggle to hit. I worked five years in manufacturing at Siemens, and this is the part people often overlook. The real magic is not new or loud. It is stability. Repeatability. Tool paths that were tuned forever. Precision that just keeps working. Robotics is in a hype cycle right now, but manufacturing has delivered quiet perfection long before anyone talked about foundation models. Sometimes the most interesting engineering is the part that does not ask for attention. —- Weekly robotics and AI insights. Subscribe free:

A simple CNC machine. Wood. A rotating tool. And yet the pattern shifts from circles to perfect hexagons with a level of accuracy most factories still struggle to hit. I worked five years in manufacturing at Siemens, and this is the part people often overlook. The real magic is not new or loud. It is stability. Repeatability. Tool paths that were tuned forever. Precision that just keeps working. Robotics is in a hype cycle right now, but manufacturing has delivered quiet perfection long before anyone talked about foundation models. Sometimes the most interesting engineering is the part that does not ask for attention. —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

164,829 次观看 • 8 个月前

Elon Musk: Manufacturing a product is ten thousand percent more work than designing it. “Manufacturing is underrated and design is overrated. People generally think of this Eureka moment, where you come up with an idea and that is it, now it is good. But there is literally a thousand percent, maybe ten thousand percent more work that goes into the production system than the thing itself. The amount of effort that goes into the design rounds down to zero, relative to the effort that goes into the manufacturing system. If people have not been in manufacturing of something relatively new, they do not understand. They think production is like a copier. This is completely false.” Starbase Tour with Everyday Astronaut, July 30, 2021.

Elon Musk: Manufacturing a product is ten thousand percent more work than designing it. “Manufacturing is underrated and design is overrated. People generally think of this Eureka moment, where you come up with an idea and that is it, now it is good. But there is literally a thousand percent, maybe ten thousand percent more work that goes into the production system than the thing itself. The amount of effort that goes into the design rounds down to zero, relative to the effort that goes into the manufacturing system. If people have not been in manufacturing of something relatively new, they do not understand. They think production is like a copier. This is completely false.” Starbase Tour with Everyday Astronaut, July 30, 2021.

ELON CLIPS

432,857 次观看 • 1 个月前

At first glance, this looks straight out of a sci-fi movie. But what makes it fascinating is that projects like this are increasingly being built by small engineering teams and independent creators not giant defense contractors. Custom robotics is evolving fast tracked mechs, insect-inspired movement, ducted fan propulsion, advanced mobility systems… all built with accessible modern tools and components. The line between “garage project” and “advanced robotics lab” is starting to blur. Genius engineering creativity… or unnecessarily overengineered? ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

At first glance, this looks straight out of a sci-fi movie. But what makes it fascinating is that projects like this are increasingly being built by small engineering teams and independent creators not giant defense contractors. Custom robotics is evolving fast tracked mechs, insect-inspired movement, ducted fan propulsion, advanced mobility systems… all built with accessible modern tools and components. The line between “garage project” and “advanced robotics lab” is starting to blur. Genius engineering creativity… or unnecessarily overengineered? ⚠️ This content is shared for informational purposes only. CTO Robotics Media is a media platform and does not own or develop the technology shown. Credit belongs to the original creators.

CTO ROBOTICS Media

28,625 次观看 • 2 个月前

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)

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 次观看 • 8 个月前

The production-ready Optimus design has been a mirage for Elon, but he's finally ready to invest in the first line at Fremont. Elon's response to the question on Optimus production target this year: - Delaying the Optimus 3 unveiling until closer to mass production, because competitors replicate each reveal with frame-by-frame analysis. - Production start target for Optimus: late July / around August 2026. - The first Optimus line will be where the current S/X line is at the Fremont factory. Final S/X batch rolls off in early May. - The S/X line can't be torn down instantly — dismantling has to start upstream (small parts production), not at final assembly. - Full dismantle of S/X line + new-line installation for Optimus + wiring + testing takes several months minimum; pulling it off in four months would be historically fast. - Refuses to predict 2026 Optimus output. New product, new line, ~10,000 unique components; ramp speed is gated by the single slowest/most troublesome component. - Initial ramp will be slow. First tasks will be simple in-factory work, then progressively more complex.

The production-ready Optimus design has been a mirage for Elon, but he's finally ready to invest in the first line at Fremont. Elon's response to the question on Optimus production target this year: - Delaying the Optimus 3 unveiling until closer to mass production, because competitors replicate each reveal with frame-by-frame analysis. - Production start target for Optimus: late July / around August 2026. - The first Optimus line will be where the current S/X line is at the Fremont factory. Final S/X batch rolls off in early May. - The S/X line can't be torn down instantly — dismantling has to start upstream (small parts production), not at final assembly. - Full dismantle of S/X line + new-line installation for Optimus + wiring + testing takes several months minimum; pulling it off in four months would be historically fast. - Refuses to predict 2026 Optimus output. New product, new line, ~10,000 unique components; ramp speed is gated by the single slowest/most troublesome component. - Initial ramp will be slow. First tasks will be simple in-factory work, then progressively more complex.

The Humanoid Hub

28,194 次观看 • 3 个月前

These machines don’t look like they build the future of AI. But they do. What you are seeing is not an industrial robot just move. It is part of the process that makes the world’s most advanced chips possible. TRUMPF laser systems are used to manufacture key components for ASML’s EUV lithography machines. ❗️Without this step, modern AI hardware would simply not exist. • They machine parts with nanometer-level precision • They enable the optics and components needed for EUV lithography • Their stability directly affects chip yield and quality • No TRUMPF lasers, no ASML EUV. No EUV, no advanced AI chips. It is easy to focus on GPUs and models. But the real bottleneck sits much deeper in the industrial stack. —- Weekly robotics and AI insights. Subscribe free:

These machines don’t look like they build the future of AI. But they do. What you are seeing is not an industrial robot just move. It is part of the process that makes the world’s most advanced chips possible. TRUMPF laser systems are used to manufacture key components for ASML’s EUV lithography machines. ❗️Without this step, modern AI hardware would simply not exist. • They machine parts with nanometer-level precision • They enable the optics and components needed for EUV lithography • Their stability directly affects chip yield and quality • No TRUMPF lasers, no ASML EUV. No EUV, no advanced AI chips. It is easy to focus on GPUs and models. But the real bottleneck sits much deeper in the industrial stack. —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

99,899 次观看 • 7 个月前

These machines don’t look like they build the future of AI. But they do. What you are seeing is not an industrial robot just move. It is part of the process that makes the world’s most advanced chips possible. TRUMPF laser systems are used to manufacture key components for ASML’s EUV lithography machines. ❗️Without this step, modern AI hardware would simply not exist. • They machine parts with nanometer-level precision • They enable the optics and components needed for EUV lithography • Their stability directly affects chip yield and quality • No TRUMPF lasers, no ASML EUV. No EUV, no advanced AI chips. It is easy to focus on GPUs and models. But the real bottleneck sits much deeper in the industrial stack. ——- Weekly robotics and AI insights. Subscribe free:

These machines don’t look like they build the future of AI. But they do. What you are seeing is not an industrial robot just move. It is part of the process that makes the world’s most advanced chips possible. TRUMPF laser systems are used to manufacture key components for ASML’s EUV lithography machines. ❗️Without this step, modern AI hardware would simply not exist. • They machine parts with nanometer-level precision • They enable the optics and components needed for EUV lithography • Their stability directly affects chip yield and quality • No TRUMPF lasers, no ASML EUV. No EUV, no advanced AI chips. It is easy to focus on GPUs and models. But the real bottleneck sits much deeper in the industrial stack. ——- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

43,033 次观看 • 7 天前

Precision gap inspection with robots Vehicle body gap and flatness checks are now handled by robotic systems instead of manual gauges. In this setup, a KUKA robot carries high-resolution sensors to scan panel gaps and surface flatness automatically during production. • Consistent, repeatable measurements • Higher inspection reliability at line speed • Less dependence on manual quality checks This kind of inspection is becoming standard wherever tolerance windows are in the sub-millimeter range. Credit: NKF Intelligent Equipment Co., Ltd. —- Weekly robotics and AI insights. Subscribe free:

Precision gap inspection with robots Vehicle body gap and flatness checks are now handled by robotic systems instead of manual gauges. In this setup, a KUKA robot carries high-resolution sensors to scan panel gaps and surface flatness automatically during production. • Consistent, repeatable measurements • Higher inspection reliability at line speed • Less dependence on manual quality checks This kind of inspection is becoming standard wherever tolerance windows are in the sub-millimeter range. Credit: NKF Intelligent Equipment Co., Ltd. —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

51,564 次观看 • 7 个月前

Physical AI hits production speed on automotive assembly! 👀 Sanctuary AI just achieved 99,5%+ success on a wire plugging task at a Tier 1 automotive supplier, 2.54 seconds per task, validated against live production benchmarks. The system matched the customer's actual production line throughput. The task sounds simple. But if you look closer, it's not. Inserting flexible wires into moving targets on a conveyor requires contact-rich dexterity, force sensing, real-time adaptation. Materials shift. Targets move. This has stayed out of reach for traditional automation. Instead of waiting for humanoid hardware to mature, Sanctuary AI is deploying Physical AI on existing commercial robotic platforms (Universal Robots in this case). So their solution is fully hardware-agnostic. Deploy today on what you already have. Scale to next-gen humanoids later. Olivia Norton (co-founder, CTO): "Physical AI adoption is gated by AI that meets both performance and cycle time requirements. That's what customers are seeking, and that's what we are delivering." Looks like manufacturing, logistics, and other labor-constrained industries don't need to wait. Read more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Physical AI hits production speed on automotive assembly! 👀 Sanctuary AI just achieved 99,5%+ success on a wire plugging task at a Tier 1 automotive supplier, 2.54 seconds per task, validated against live production benchmarks. The system matched the customer's actual production line throughput. The task sounds simple. But if you look closer, it's not. Inserting flexible wires into moving targets on a conveyor requires contact-rich dexterity, force sensing, real-time adaptation. Materials shift. Targets move. This has stayed out of reach for traditional automation. Instead of waiting for humanoid hardware to mature, Sanctuary AI is deploying Physical AI on existing commercial robotic platforms (Universal Robots in this case). So their solution is fully hardware-agnostic. Deploy today on what you already have. Scale to next-gen humanoids later. Olivia Norton (co-founder, CTO): "Physical AI adoption is gated by AI that meets both performance and cycle time requirements. That's what customers are seeking, and that's what we are delivering." Looks like manufacturing, logistics, and other labor-constrained industries don't need to wait. Read more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

45,757 次观看 • 1 个月前

A GUY PUT GPT-LEVEL AI INSIDE A 3D PRINTED ROBOT AND RELEASED THE ENTIRE THING FOR FREE Most people look at a 3D printer and see plastic toys This guy printed a robot with expressive eyes, object tracking, image recognition, support for ChatGPT, Qwen and offline models, then uploaded the STL files, code and hardware designs for anyone to build themselves The interesting part isn't the robot It's how fast the gap between "I have an idea" and "I built a working product" is disappearing A few years ago this required a team of engineers Now one person with a printer, open-source software and enough curiosity can build something that looks like it came from a robotics startup We're getting very close to a world where manufacturing, AI and robotics stop being separate industries and start becoming the same thing

A GUY PUT GPT-LEVEL AI INSIDE A 3D PRINTED ROBOT AND RELEASED THE ENTIRE THING FOR FREE Most people look at a 3D printer and see plastic toys This guy printed a robot with expressive eyes, object tracking, image recognition, support for ChatGPT, Qwen and offline models, then uploaded the STL files, code and hardware designs for anyone to build themselves The interesting part isn't the robot It's how fast the gap between "I have an idea" and "I built a working product" is disappearing A few years ago this required a team of engineers Now one person with a printer, open-source software and enough curiosity can build something that looks like it came from a robotics startup We're getting very close to a world where manufacturing, AI and robotics stop being separate industries and start becoming the same thing

lagerskoy

57,099 次观看 • 2 个月前

An ultra compact, high precision industrial robot arm. This one stood out to me because it targets a part of automation that is usually glossed over. Extreme precision in very small spaces. According to Oleksandr Stepanenko, the arm is designed from the ground up with fully custom electronics, software, and calibration, paired with industrial components from Harmonic Drive and maxon. Reported specs are notable: • Repeatability better than 0.001 mm • Payload 250 g • Reach 250 mm • Total mass 1.5 kg This kind of form factor opens up use cases that traditional industrial arms struggle with. Think PCB assembly, micro soldering, precision pick and place of irregular parts, and medical or micro robotics components. ❗️What I find interesting is not just the numbers, but the direction… Smaller, lighter, highly precise systems could unlock automation in environments where space, inertia, and tolerance are the real constraints. Credit to Oleksandr Stepanenko for the original work and post. —- Weekly robotics and AI insights. Subscribe free:

An ultra compact, high precision industrial robot arm. This one stood out to me because it targets a part of automation that is usually glossed over. Extreme precision in very small spaces. According to Oleksandr Stepanenko, the arm is designed from the ground up with fully custom electronics, software, and calibration, paired with industrial components from Harmonic Drive and maxon. Reported specs are notable: • Repeatability better than 0.001 mm • Payload 250 g • Reach 250 mm • Total mass 1.5 kg This kind of form factor opens up use cases that traditional industrial arms struggle with. Think PCB assembly, micro soldering, precision pick and place of irregular parts, and medical or micro robotics components. ❗️What I find interesting is not just the numbers, but the direction… Smaller, lighter, highly precise systems could unlock automation in environments where space, inertia, and tolerance are the real constraints. Credit to Oleksandr Stepanenko for the original work and post. —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

74,345 次观看 • 8 个月前

People who've never set foot in a factory will never understand... I watched this three times. For decades, robotics simulation has promised faster deployment. But factories still had to build the real cell to see if it actually worked. Which meant expensive physical prototypes, weeks or months!!! of commissioning, constant surprises between simulation and reality That “sim-to-real gap” has quietly been one of the biggest bottlenecks in manufacturing automation. And it’s exactly what is changing. Today, ABB Robotics announced a partnership with NVIDIA Robotics aimed at closing this gap through the new RobotStudio HyperReality platform: Simulation and real robot behavior can match with near-perfect accuracy. That means manufacturers can design, test, and validate entire production lines before a single robot is installed on the factory floor. The implications are massive: • up to 80% faster setup and commissioning • roughly 40% lower costs by removing physical prototypes • about 50% faster time-to-market for new production lines In other words: Factories can move from trial-and-error engineering to software-driven manufacturing design. Production lines become something you build and validate digitally first. Then deploy physically once everything already works. For an industry that still measures deployment timelines in months or years, this is a major shift. It changes how automation projects are planned, how factories are designed, and how fast manufacturing can adapt to new products. Physical AI actually becomes deployable at an industrial scale. I’ll be at GTC in San Jose next week to see and talk to manufacturers and robotics engineers. If you are into manufacturing like I am, hit me up; my DMs are open!

People who've never set foot in a factory will never understand... I watched this three times. For decades, robotics simulation has promised faster deployment. But factories still had to build the real cell to see if it actually worked. Which meant expensive physical prototypes, weeks or months!!! of commissioning, constant surprises between simulation and reality That “sim-to-real gap” has quietly been one of the biggest bottlenecks in manufacturing automation. And it’s exactly what is changing. Today, ABB Robotics announced a partnership with NVIDIA Robotics aimed at closing this gap through the new RobotStudio HyperReality platform: Simulation and real robot behavior can match with near-perfect accuracy. That means manufacturers can design, test, and validate entire production lines before a single robot is installed on the factory floor. The implications are massive: • up to 80% faster setup and commissioning • roughly 40% lower costs by removing physical prototypes • about 50% faster time-to-market for new production lines In other words: Factories can move from trial-and-error engineering to software-driven manufacturing design. Production lines become something you build and validate digitally first. Then deploy physically once everything already works. For an industry that still measures deployment timelines in months or years, this is a major shift. It changes how automation projects are planned, how factories are designed, and how fast manufacturing can adapt to new products. Physical AI actually becomes deployable at an industrial scale. I’ll be at GTC in San Jose next week to see and talk to manufacturers and robotics engineers. If you are into manufacturing like I am, hit me up; my DMs are open!

Ilir Aliu

68,927 次观看 • 5 个月前

$Most robotics teams can make a robot move… very few can make it work every day in the real world! @roboforce_inc was just featured in Jensen Huang’s GTC keynote, not for a demo but for a robot they claim is already working in the field. Their system, TITAN, is built for industrial environments: ✅ 40 kg dual-arm payload ✅ millimeter-level precision ✅ 8 hours runtime ✅ early pilots in energy, logistics, and manufacturing They call it Physical AI: The focus is on getting robots to do the kind of labor that still depends on people: repetitive, risky, and physical. IMO, what stands out isn’t the specs. It’s the claim of 11,000 robot orders❗️ If even a fraction of that turns into real deployments, it would make RoboForce one of the most widely scaled robot platforms in the world!!?? The open question is whether this shift from prototype to production is real or just the next phase of robotics storytelling. It looks very promising to me. It’s also interesting how their founder openly pushes back against the humanoid trend, arguing for wheels over legs in real industrial settings. It’s an unusual perspective in a time when humanoids get most of the attention. If they are right, the next humanoid robotics wave might look less like a human and more like an industrial version. Seen at —- Weekly robotics and AI insights. Subscribe free:$

Most robotics teams can make a robot move… very few can make it work every day in the real world! @roboforce_inc was just featured in Jensen Huang’s GTC keynote, not for a demo but for a robot they claim is already working in the field. Their system, TITAN, is built for industrial environments: ✅ 40 kg dual-arm payload ✅ millimeter-level precision ✅ 8 hours runtime ✅ early pilots in energy, logistics, and manufacturing They call it Physical AI: The focus is on getting robots to do the kind of labor that still depends on people: repetitive, risky, and physical. IMO, what stands out isn’t the specs. It’s the claim of 11,000 robot orders❗️ If even a fraction of that turns into real deployments, it would make RoboForce one of the most widely scaled robot platforms in the world!!?? The open question is whether this shift from prototype to production is real or just the next phase of robotics storytelling. It looks very promising to me. It’s also interesting how their founder openly pushes back against the humanoid trend, arguing for wheels over legs in real industrial settings. It’s an unusual perspective in a time when humanoids get most of the attention. If they are right, the next humanoid robotics wave might look less like a human and more like an industrial version. Seen at —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

27,741 次观看 • 9 个月前

TESLA'S UNBOXED REVOLUTION: FIRST GLIMPSE OF CYBERCAB ASSEMBLY LINE Tesla's unboxed manufacturing process is in full swing. With yellow bots swarming like a sci-fi symphony to slap together Cybercab chassis, suspensions, and bodies in parallel zones instead of the old-school conveyor belt drag. Gone are the days of linear assembly lines; this modular magic builds sections simultaneously, then snaps 'em together for lightning-fast production. We're talking front, rear, doors, and interiors all getting love at once, cutting build time by up to 50% and costs by 30% for those sweet $20K Robotaxis. Elon's masterplan? Flood the streets with affordable EVs and autonomous rides, turning factories into efficiency beasts. And that zonal wiring? Key to making it all click without the mess, only Tesla and Rivian are playing at this level. If this scales, it's game over for legacy auto. Cheaper, faster, greener wheels incoming. Hype level: Over 9000! Source: Luca Greco, Electrek, AMS, Tesla

TESLA'S UNBOXED REVOLUTION: FIRST GLIMPSE OF CYBERCAB ASSEMBLY LINE Tesla's unboxed manufacturing process is in full swing. With yellow bots swarming like a sci-fi symphony to slap together Cybercab chassis, suspensions, and bodies in parallel zones instead of the old-school conveyor belt drag. Gone are the days of linear assembly lines; this modular magic builds sections simultaneously, then snaps 'em together for lightning-fast production. We're talking front, rear, doors, and interiors all getting love at once, cutting build time by up to 50% and costs by 30% for those sweet $20K Robotaxis. Elon's masterplan? Flood the streets with affordable EVs and autonomous rides, turning factories into efficiency beasts. And that zonal wiring? Key to making it all click without the mess, only Tesla and Rivian are playing at this level. If this scales, it's game over for legacy auto. Cheaper, faster, greener wheels incoming. Hype level: Over 9000! Source: Luca Greco, Electrek, AMS, Tesla

Mario Nawfal

228,198 次观看 • 9 个月前

Finally. After 18 months of patience, FSD is officially approved and live in the Netherlands. I’ve been driving with it for 2 days now. And the experience is on another level. It feels like the future unfolding in real time. The precision. The intelligence. The confidence of the system. This is not incremental progress. This is a clear step forward in how mobility works. Huge thanks to Elon Musk and the entire AI team at Tesla. From a professional perspective, this shows what is possible when software, data, and real-world deployment come together at scale. The question is no longer if this will take over. The question is how fast it will expand. This is a turning point. Elon Musk

Finally. After 18 months of patience, FSD is officially approved and live in the Netherlands. I’ve been driving with it for 2 days now. And the experience is on another level. It feels like the future unfolding in real time. The precision. The intelligence. The confidence of the system. This is not incremental progress. This is a clear step forward in how mobility works. Huge thanks to Elon Musk and the entire AI team at Tesla. From a professional perspective, this shows what is possible when software, data, and real-world deployment come together at scale. The question is no longer if this will take over. The question is how fast it will expand. This is a turning point. Elon Musk

NL F$D Inside

25,130,079 次观看 • 4 个月前

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

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

Patrick OShaughnessy

50,988 次观看 • 5 个月前

Despite the latest controversy, I want Ola Electric to succeed. This is will only accelerate manufacturing in India. Yes, a lot of spare parts of Ola scooties are imported from China but you can’t do much at this point- you start with assembly and slowly whole ecosystem is built around with SMEs producing and supplying key components. Ola is doing at least some in-house manufacturing, that’s how they got PLI. Tata Nixon right now is the best selling EV; one time it used to frequently catch fire but they fixed it. I hope Bhavish Aggarwal spends time understanding genuine complaints and fix the products in due time instead of picking fights off twitter. Ola has distribution and production capacity, they need to fix some quality issues, hope Bhavish get down to business. Here is video of Ola electric factory.

Despite the latest controversy, I want Ola Electric to succeed. This is will only accelerate manufacturing in India. Yes, a lot of spare parts of Ola scooties are imported from China but you can’t do much at this point- you start with assembly and slowly whole ecosystem is built around with SMEs producing and supplying key components. Ola is doing at least some in-house manufacturing, that’s how they got PLI. Tata Nixon right now is the best selling EV; one time it used to frequently catch fire but they fixed it. I hope Bhavish Aggarwal spends time understanding genuine complaints and fix the products in due time instead of picking fights off twitter. Ola has distribution and production capacity, they need to fix some quality issues, hope Bhavish get down to business. Here is video of Ola electric factory.

Shark

84,381 次观看 • 1 年前

The Cybercab is aiming to produce 2 million units per year. Let this sink in. Today, Tesla produces about ~1.7 million vehicles per year total, across its entire lineup. And now Tesla is preparing to outproduce that with one single vehicle, a fully autonomous one. This is Elon and Tesla going ALL-IN on autonomy. Production is scheduled to start April 2026 at Giga Texas, with volume ramping throughout the year. And as of early 2026, Cybercab prototypes are already being tested around the U.S. The Tesla Cybercab is built from the ground up for unsupervised autonomy. There is no steering wheel and no pedals, just cameras, AI, and Tesla’s custom inference computers. No lidar and radar like other companies, just pure vision and software. Elon put it best on the Q3 2024 earnings call: “It’s not just a revolutionary vehicle design, but a revolution in vehicle manufacturing that is also coming with the Cybercab.” That quote matters a lot bc that means the entire way a vehicle is manufactured is changing with the Cybercab. Tesla is designing what Elon calls “the machine that builds the machine.” The Cybercab uses Tesla’s unboxed manufacturing process, where major sections are built in parallel instead of one long assembly line. There are fewer parts, less steps & cost, and faster scale. That’s how you make 2 million Cybercabs per year possible. FYI, this is not going to be easy though. Elon has been brutally honest about production for many years: • “Prototypes are easy, production is hard.” • “The extreme difficulty of scaling production of new technology is poorly understood. It’s 1000% to 10,000% harder than making a few prototypes.” • “For cars, it’s maybe 100 times harder to design the manufacturing system than the car itself.” He reinforced this again in January 2026 when talking about Cybercab and Optimus on 𝕏: “Initial production is always very slow and follows an S-curve. The speed of the production ramp is inversely proportional to how many new parts and steps there are. For Cybercab and Optimus, almost everything is new, so the early production rate will be agonizingly slow - but eventually end up being insanely fast.” This is the key thing most people miss about Tesla manufacturing. Early output will be slow by design. Almost everything is new like the vehicle architecture, factory layout, AI hardware, and manufacturing flow. But once it works and clicks, it begins to scale hard. Tesla already proved they can do this. They survived Model 3 production hell. They turned Model Y into the BEST selling car in the world, of any kind. They ramped Cybertruck, which has over 30,000+ unique parts, to meaningful volume. Elon summed it up perfectly in 2024: “Compared to the insane pain of reaching high volume, positive margin production, prototypes are a piece of cake.” That’s why Tesla makes manufacturing look easy bc they already earned the scars from the last vehicle lineups. The Cybercab is aiming to be: 1/ Under $30,000 price 2/ ~$0.20 per mile operating cost 3/ 200+ mile range 4/ Up to 5x utilization vs personal cars 5/ Designed to run nearly nonstop 24/7 This is what you call manufacturing + AI + autonomy converging at scale. The competitors are still showing prototypes and demos, while Tesla is building new production lines, expanding factories, and actually building the product. I remember when Elon told me in the past that one of Tesla’s key advantage long term was going to be manufacturing technology. I get it now.

The Cybercab is aiming to produce 2 million units per year. Let this sink in. Today, Tesla produces about ~1.7 million vehicles per year total, across its entire lineup. And now Tesla is preparing to outproduce that with one single vehicle, a fully autonomous one. This is Elon and Tesla going ALL-IN on autonomy. Production is scheduled to start April 2026 at Giga Texas, with volume ramping throughout the year. And as of early 2026, Cybercab prototypes are already being tested around the U.S. The Tesla Cybercab is built from the ground up for unsupervised autonomy. There is no steering wheel and no pedals, just cameras, AI, and Tesla’s custom inference computers. No lidar and radar like other companies, just pure vision and software. Elon put it best on the Q3 2024 earnings call: “It’s not just a revolutionary vehicle design, but a revolution in vehicle manufacturing that is also coming with the Cybercab.” That quote matters a lot bc that means the entire way a vehicle is manufactured is changing with the Cybercab. Tesla is designing what Elon calls “the machine that builds the machine.” The Cybercab uses Tesla’s unboxed manufacturing process, where major sections are built in parallel instead of one long assembly line. There are fewer parts, less steps & cost, and faster scale. That’s how you make 2 million Cybercabs per year possible. FYI, this is not going to be easy though. Elon has been brutally honest about production for many years: • “Prototypes are easy, production is hard.” • “The extreme difficulty of scaling production of new technology is poorly understood. It’s 1000% to 10,000% harder than making a few prototypes.” • “For cars, it’s maybe 100 times harder to design the manufacturing system than the car itself.” He reinforced this again in January 2026 when talking about Cybercab and Optimus on 𝕏: “Initial production is always very slow and follows an S-curve. The speed of the production ramp is inversely proportional to how many new parts and steps there are. For Cybercab and Optimus, almost everything is new, so the early production rate will be agonizingly slow - but eventually end up being insanely fast.” This is the key thing most people miss about Tesla manufacturing. Early output will be slow by design. Almost everything is new like the vehicle architecture, factory layout, AI hardware, and manufacturing flow. But once it works and clicks, it begins to scale hard. Tesla already proved they can do this. They survived Model 3 production hell. They turned Model Y into the BEST selling car in the world, of any kind. They ramped Cybertruck, which has over 30,000+ unique parts, to meaningful volume. Elon summed it up perfectly in 2024: “Compared to the insane pain of reaching high volume, positive margin production, prototypes are a piece of cake.” That’s why Tesla makes manufacturing look easy bc they already earned the scars from the last vehicle lineups. The Cybercab is aiming to be: 1/ Under $30,000 price 2/ ~$0.20 per mile operating cost 3/ 200+ mile range 4/ Up to 5x utilization vs personal cars 5/ Designed to run nearly nonstop 24/7 This is what you call manufacturing + AI + autonomy converging at scale. The competitors are still showing prototypes and demos, while Tesla is building new production lines, expanding factories, and actually building the product. I remember when Elon told me in the past that one of Tesla’s key advantage long term was going to be manufacturing technology. I get it now.

Teslaconomics

31,985 次观看 • 6 个月前