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I like this gradual, step-by-step process. Last year, UBTECH’s Liuzhou factory rolled out its 1,000th humanoid robot. It has since moved from a 1,000-unit production line toward a 10,000-unit capacity,now. There’s no grand promise of mass production here. Just a practical, steady push. It’s a manufacturing strategy responding to... show more

CyberRobo

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24,070 views • 1 day ago •via X (Twitter)

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TESLA HALTED MODEL S AND MODEL X PRODUCTION TO BUILD AN ARMY OF OPTIMUS ROBOTS The Fremont assembly line was torn down in 46 days. In its place, Tesla is building a line for humanoid production, aiming for a million units a year A humanoid robot is a body shaped like a human. Physical AI is the intelligence that controls that body Walking and making coffee is often just imitation learning from a scripted routine. But once the environment shifts, the learned trick stops working Language models had the entire internet to train on. Robotics has nothing close to that scale of data, which is why one giant brain hasn't worked for anyone yet The industry is moving toward modularity instead - separate models for vision, movement, and planning, each improved on its own The real question is no longer whether a robot can move impressively. It's whether it can pull its sensors into one picture of the world and adapt to whatever wasn't scripted for it

TESLA HALTED MODEL S AND MODEL X PRODUCTION TO BUILD AN ARMY OF OPTIMUS ROBOTS The Fremont assembly line was torn down in 46 days. In its place, Tesla is building a line for humanoid production, aiming for a million units a year A humanoid robot is a body shaped like a human. Physical AI is the intelligence that controls that body Walking and making coffee is often just imitation learning from a scripted routine. But once the environment shifts, the learned trick stops working Language models had the entire internet to train on. Robotics has nothing close to that scale of data, which is why one giant brain hasn't worked for anyone yet The industry is moving toward modularity instead - separate models for vision, movement, and planning, each improved on its own The real question is no longer whether a robot can move impressively. It's whether it can pull its sensors into one picture of the world and adapt to whatever wasn't scripted for it

iamigorekk

22,205 views • 28 days ago

🚨 AMERICA JUST BUILT THE WORLD’S MOST POWERFUL METAL 3D PRINTER AND IT’S ABOUT TO MASS-PRODUCE ROCKETS AND MISSILES. Divergent Technologies has unveiled the Monolith One, a giant industrial metal printer standing over 8 meters tall and armed with 12 high-powered lasers delivering a combined 24 kilowatts of energy. Unlike typical 3D printers used for prototypes, this machine is built for serious, high-volume production. It can print large, complex aerospace and defense parts in aluminum, titanium, steel, and nickel alloys and it roughly doubles the output of current systems. Why this matters: • Divergent plans to install 64 more of these machines in a massive new 430,000 sq ft factory in Long Beach, California • Once running, the facility aims to produce tens of thousands of munition airframes per year plus hundreds of thousands of critical metal components • It slashes manufacturing time from months down to weeks or even days • The company already supplies major players like Lockheed Martin and RTX The deeper implication: This isn’t just another 3D printer. It represents a shift toward software-defined, on-demand manufacturing at industrial scale for mission-critical hardware. As defense and aerospace demand skyrockets, traditional supply chains are too slow. Systems like Monolith One could become a cornerstone of faster, more resilient domestic production especially for complex structures that are difficult or impossible to make conventionally. We’re watching the industrialization of additive manufacturing in real time. How do you think large-scale 3D printing will change aerospace and defense manufacturing over the next decade? Follow for more frontier manufacturing and defense technology.

🚨 AMERICA JUST BUILT THE WORLD’S MOST POWERFUL METAL 3D PRINTER AND IT’S ABOUT TO MASS-PRODUCE ROCKETS AND MISSILES. Divergent Technologies has unveiled the Monolith One, a giant industrial metal printer standing over 8 meters tall and armed with 12 high-powered lasers delivering a combined 24 kilowatts of energy. Unlike typical 3D printers used for prototypes, this machine is built for serious, high-volume production. It can print large, complex aerospace and defense parts in aluminum, titanium, steel, and nickel alloys and it roughly doubles the output of current systems. Why this matters: • Divergent plans to install 64 more of these machines in a massive new 430,000 sq ft factory in Long Beach, California • Once running, the facility aims to produce tens of thousands of munition airframes per year plus hundreds of thousands of critical metal components • It slashes manufacturing time from months down to weeks or even days • The company already supplies major players like Lockheed Martin and RTX The deeper implication: This isn’t just another 3D printer. It represents a shift toward software-defined, on-demand manufacturing at industrial scale for mission-critical hardware. As defense and aerospace demand skyrockets, traditional supply chains are too slow. Systems like Monolith One could become a cornerstone of faster, more resilient domestic production especially for complex structures that are difficult or impossible to make conventionally. We’re watching the industrialization of additive manufacturing in real time. How do you think large-scale 3D printing will change aerospace and defense manufacturing over the next decade? Follow for more frontier manufacturing and defense technology.

TheNewPhysics

80,575 views • 2 months ago

JACK JUST ORDERED 2,000 HUMANOID ROBOTS. SOFT FABRIC WAS SUPPOSED TO BE THE ONE THING ROBOTS COULDN’T HANDLE.🤖👕 Sewing has always been the automation-proof job. Cloth wrinkles, shifts, deforms — machines are built for rigid parts, not soft ones. Now watch the clip. Alignment deviations for cut pieces like collars and pockets have to stay within ±2mm. Cutting and sewing motions demand 0.3-0.5mm precision — tighter tolerances than most metal assembly work. Robots on this line are already hitting 98% fabric-separation accuracy, running 3-second operations, and reaching 80% of human efficiency. They’re not alone at the machines. Real workers sit right beside them, running the same Juki and Jack stations, same shift. A Jack executive was upfront: the robots can currently perform individual sewing operations, not run a complete production line independently. This is task automation, not a fully autonomous tailor. But it’s real, and it’s running on an active factory floor. Jack Technology has now ordered 2,000 of these units for apparel manufacturing — aiming to lift manufacturing efficiency by at least 30% across the line. Ten years ago, “robot-proof job” was the whole pitch for garment work. That pitch just expired. Would a 2,000-robot rollout change where your clothes get made?

JACK JUST ORDERED 2,000 HUMANOID ROBOTS. SOFT FABRIC WAS SUPPOSED TO BE THE ONE THING ROBOTS COULDN’T HANDLE.🤖👕 Sewing has always been the automation-proof job. Cloth wrinkles, shifts, deforms — machines are built for rigid parts, not soft ones. Now watch the clip. Alignment deviations for cut pieces like collars and pockets have to stay within ±2mm. Cutting and sewing motions demand 0.3-0.5mm precision — tighter tolerances than most metal assembly work. Robots on this line are already hitting 98% fabric-separation accuracy, running 3-second operations, and reaching 80% of human efficiency. They’re not alone at the machines. Real workers sit right beside them, running the same Juki and Jack stations, same shift. A Jack executive was upfront: the robots can currently perform individual sewing operations, not run a complete production line independently. This is task automation, not a fully autonomous tailor. But it’s real, and it’s running on an active factory floor. Jack Technology has now ordered 2,000 of these units for apparel manufacturing — aiming to lift manufacturing efficiency by at least 30% across the line. Ten years ago, “robot-proof job” was the whole pitch for garment work. That pitch just expired. Would a 2,000-robot rollout change where your clothes get made?

DN_DEGEN

28,317 views • 1 month ago

Most humanoid projects talk about real work. Very few last an hour on a real line. This week I saw a case that matters for anyone building robots, perception, or physical AI. Kinisi deployed its first mobile manipulation system into a live recycling facility. Not a demo. Not a staged test. A real production line with real output pressure. Why this matters if you want robotics to deliver real value on your floor: • Handles mixed glass with random poses and no fixed fixtures. • Runs real grasp selection under noise, vibration and production variability. • Maintains throughput while avoiding breakage on a delicate material. • Shows mobile manipulation doing actual shift work instead of controlled lab runs. Kinisi published a video that shows what the robot sees and how sensor data turns into action. This is the part most teams struggle to explain to customers, so the educational angle is useful for anyone working on adoption. On top of this, the team signed a pilot with a global automotive manufacturer to explore humanoid use cases in production. The direction is clear. Wheeled mobility (not legs!) plus strong perception seems to be shaping a large part of industrial humanoids right now. I know Brennand from earlier conversations and from our podcast session, and I am always glad to see European teams push the category forward. Wishing the Kinisi team continued success. —- Weekly robotics and AI insights. Subscribe free:

Most humanoid projects talk about real work. Very few last an hour on a real line. This week I saw a case that matters for anyone building robots, perception, or physical AI. Kinisi deployed its first mobile manipulation system into a live recycling facility. Not a demo. Not a staged test. A real production line with real output pressure. Why this matters if you want robotics to deliver real value on your floor: • Handles mixed glass with random poses and no fixed fixtures. • Runs real grasp selection under noise, vibration and production variability. • Maintains throughput while avoiding breakage on a delicate material. • Shows mobile manipulation doing actual shift work instead of controlled lab runs. Kinisi published a video that shows what the robot sees and how sensor data turns into action. This is the part most teams struggle to explain to customers, so the educational angle is useful for anyone working on adoption. On top of this, the team signed a pilot with a global automotive manufacturer to explore humanoid use cases in production. The direction is clear. Wheeled mobility (not legs!) plus strong perception seems to be shaping a large part of industrial humanoids right now. I know Brennand from earlier conversations and from our podcast session, and I am always glad to see European teams push the category forward. Wishing the Kinisi team continued success. —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

24,802 views • 9 months ago

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TheNewPhysics

13,612 views • 3 months ago

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A machine like this can cost $500,000 to well over $1 million to make parts that may be worth only $10-15 This is the real manufacturing story. This INDEX six-spindle automatic carries 6 motorised spindles, up to 12 CNC tool carriers, operates at 8,000+ rpm, and weighs 7.2 tonnes. Different operations happen simultaneously as the spindle drum indexes each workpiece from station to station. A real scale production example produced a precision component in 11 seconds, versus 38 seconds on a conventional single-spindle lathe. That's roughly 327 parts per hour before downtime. But the machine is only the hardware. Tool geometry, CNC programs, cutting parameters, spindle synchronisation, tooling, bar feeding, chip evacuation, coolant, inspection and collision checked simulation all have to be engineered around the exact part. That is what it takes to integrate this machine into a factory workflow. This accumulated capability is what kept Germany and Japan at the pinnacle of machine-tool manufacturing for decades almost unchallenged. The advantage wasn't just building the hardware, but knowing how to program, tool and integrate these machines for thousands of different manufacturing requirements globally. China has now built much of that ecosystem at extraordinary scale, machines, controls, tooling, software, automation and integration. Its huge domestic manufacturing base has accelerated that learning curve dramatically. Today, Chinese manufacturers can increasingly offer sophisticated CNC and multi-spindle systems at 30-40% lower total costs in most applications, putting serious and relentless price pressure on German and Japanese builders. China produced 37% of the world's machine tools in 2025, compared with 12% for Germany and 10% for Japan. These are the machines that make the machines and ultimately determine how much an economy can manufacture. China is the biggest player as of now and growing faster than anyone else in manufacturing high-end machining tools. Source, Daniel Jansson

Ammanichanda

38,359 views • 1 month ago

🚨 SPACEX IS ABOUT TO TEST A RADICALLY DIFFERENT KIND OF SPACECRAFT AND IT COULD UPEND THE ENTIRE ORBITAL MANUFACTURING INDUSTRY. On Tuesday, SpaceX plans to fly the first prototype of Starfall, a flat, disk-shaped reentry capsule designed to return up to 1,000 kilograms of cargo from orbit in a single flight. That’s roughly 30 times more payload capacity than current commercial return vehicles (like those from Varda Space Industries). It’s not a scaled-down Dragon it’s a completely different approach: no onboard deorbit engine, a wide flat disk geometry, and Starlink terminals mounted to maintain communication through the plasma blackout during reentry. Why this matters: • Current orbital manufacturing companies are limited to returning only dozens of kilograms per mission • Starfall’s design could make large-scale commercial production in space economically viable for the first time • SpaceX would be directly competing with companies (like Varda) that currently pay SpaceX to launch their capsules • Successfully testing Starlink through reentry plasma would be a major technical win with applications across SpaceX’s vehicles The deeper implication: SpaceX is quietly expanding its vertical integration. They already dominate launch. Now they’re moving into the return leg of the orbital manufacturing supply chain the part that has been the biggest bottleneck for companies trying to make products in microgravity and bring them back to Earth. If Starfall works at scale, it doesn’t just give SpaceX another revenue stream. It gives them significant control over the economics of an entire emerging industry. The disk shape and high-capacity design suggest they’re thinking about high-cadence, lower-cost returns rather than the traditional high-value, low-volume approach. This is classic SpaceX: take an existing problem (expensive, low-capacity return from orbit), apply first-principles thinking to the vehicle design, and try to make it dramatically cheaper and higher volume. How do you think this move into orbital return changes the competitive landscape for companies trying to build businesses in space manufacturing? Follow for more analysis on SpaceX’s expanding role across the space economy.

🚨 SPACEX IS ABOUT TO TEST A RADICALLY DIFFERENT KIND OF SPACECRAFT AND IT COULD UPEND THE ENTIRE ORBITAL MANUFACTURING INDUSTRY. On Tuesday, SpaceX plans to fly the first prototype of Starfall, a flat, disk-shaped reentry capsule designed to return up to 1,000 kilograms of cargo from orbit in a single flight. That’s roughly 30 times more payload capacity than current commercial return vehicles (like those from Varda Space Industries). It’s not a scaled-down Dragon it’s a completely different approach: no onboard deorbit engine, a wide flat disk geometry, and Starlink terminals mounted to maintain communication through the plasma blackout during reentry. Why this matters: • Current orbital manufacturing companies are limited to returning only dozens of kilograms per mission • Starfall’s design could make large-scale commercial production in space economically viable for the first time • SpaceX would be directly competing with companies (like Varda) that currently pay SpaceX to launch their capsules • Successfully testing Starlink through reentry plasma would be a major technical win with applications across SpaceX’s vehicles The deeper implication: SpaceX is quietly expanding its vertical integration. They already dominate launch. Now they’re moving into the return leg of the orbital manufacturing supply chain the part that has been the biggest bottleneck for companies trying to make products in microgravity and bring them back to Earth. If Starfall works at scale, it doesn’t just give SpaceX another revenue stream. It gives them significant control over the economics of an entire emerging industry. The disk shape and high-capacity design suggest they’re thinking about high-cadence, lower-cost returns rather than the traditional high-value, low-volume approach. This is classic SpaceX: take an existing problem (expensive, low-capacity return from orbit), apply first-principles thinking to the vehicle design, and try to make it dramatically cheaper and higher volume. How do you think this move into orbital return changes the competitive landscape for companies trying to build businesses in space manufacturing? Follow for more analysis on SpaceX’s expanding role across the space economy.

TheNewPhysics

445,776 views • 2 months ago

$ai ads already look exactly like normal ads this could be a real pet clip a normal living room product shot or a casual phone-style review same structure, same pacing, same emotional cues they convert the same as traditional creatives but cost a fraction and take hours instead of weeks to produce when ai blends into the feed performance doesn’t drop production friction does i broke down how to build ai ads that are indistinguishable from real ones and how to use them to scale faster with lower costs rt + comment “blend” and i’ll send the breakdown (follow for dm)$

ai ads already look exactly like normal ads this could be a real pet clip a normal living room product shot or a casual phone-style review same structure, same pacing, same emotional cues they convert the same as traditional creatives but cost a fraction and take hours instead of weeks to produce when ai blends into the feed performance doesn’t drop production friction does i broke down how to build ai ads that are indistinguishable from real ones and how to use them to scale faster with lower costs rt + comment “blend” and i’ll send the breakdown (follow for dm)

Alessandro

13,253 views • 8 months ago

two weeks in Shenzhen and it’s an been eye-opening experience im here for a month with MIT SCALE and the speed of hardware production is easily 10× faster than sf. from product concept to production, everything is streamlined within a single building. Nearly every component you could need is available immediately thru Taobao(e bay of China) or HQB and there are 24/7 makerspaces equipped to build anything from micrometer-scale PCBs to full assembly-line robots. What’s striking is that Shenzhen already has much of the hardware and robotics that startups in sf are still trying to build except these systems have been deployed and operating for years. The manufacturing capability, supply chain depth, and technical execution here are world-class. That said, one gap keeps surfacing: brand design, storytelling, and cohesive user experience. Software polish, UX consistency, and attention to detail often feel secondary. Take this with a grain of salt, but it increasingly feels like the company that pairs Shenzhen-level hardware velocity with strong design sensibility and UX-first thinking will dominate the market.

Miyu Horiuchi

149,572 views • 8 months ago

Hey #NeuraxonMini is literally out! , we manage to "transplant" a Neuraxon 2 bioinspired #AI brain to a physical robot the #SpheroMini moving from our last Scientific Paper (link bellow) by David Vivancos - e/acc & Jose Sánchez for Qubic #OpenScience hybridized with #Aigarth to the real World. First you need a Sphero Education Mini robot about 50$ Then you can try the first cool demos at Hugging Face: 1.- Neuraxon2MiniControl to drive the sphero robot 2.- Neuraxon2MiniWrite to write letters or words with physical moves of the sphero robot using Neuraxon Video Tutorials on youtube later today. Why this matters? Remember we are not building "dead" LLMs we are building #AliveAIs and for that we need to explore how it behaves in reality, from how it learns to how it fails, and what better way that in the emerging field of #robotics , time will tell if your next #HumanoidRobot have a #Neuraxon brain... Read the Paper: Explore the Neuraxon code here: Are you ready for #TrueAI ?

Hey #NeuraxonMini is literally out! , we manage to "transplant" a Neuraxon 2 bioinspired #AI brain to a physical robot the #SpheroMini moving from our last Scientific Paper (link bellow) by David Vivancos - e/acc & Jose Sánchez for Qubic #OpenScience hybridized with #Aigarth to the real World. First you need a Sphero Education Mini robot about 50$ Then you can try the first cool demos at Hugging Face: 1.- Neuraxon2MiniControl to drive the sphero robot 2.- Neuraxon2MiniWrite to write letters or words with physical moves of the sphero robot using Neuraxon Video Tutorials on youtube later today. Why this matters? Remember we are not building "dead" LLMs we are building #AliveAIs and for that we need to explore how it behaves in reality, from how it learns to how it fails, and what better way that in the emerging field of #robotics , time will tell if your next #HumanoidRobot have a #Neuraxon brain... Read the Paper: Explore the Neuraxon code here: Are you ready for #TrueAI ?

David Vivancos - e/acc

29,293 views • 6 months ago

🦿Xpeng showed a humanoid robot called IRON whose movement looked so human that the team literally cut it open on stage to prove it is a machine. IRON uses a bionic body with a flexible spine, synthetic muscles, and soft skin so joints and torso can twist smoothly like a person. The system has 82 degrees of freedom in total with 22 in each hand for fine finger control. Compute runs on 3 custom AI chips rated at 2,250 TOPS (Tera Operations Per Second), which is far above typical laptop neural accelerators, so it can handle vision and motion planning on the robot. The AI stack focuses on turning camera input directly into body movement without routing through text, which reduces lag and makes the gait look natural. Xpeng staged the cut-open demo at AI Day in Guangzhou this week, addressing rumors that a performer was inside by exposing internal actuators, wiring, and cooling. Company materials also mention a large physical-world model and a multi-brain control setup for dialogue, perception, and locomotion, hinting at a path from stage demos to service work. Production is targeted for 2026, so near-term tasks will be limited, but the hardware shows a serious step toward human-scale manipulation.

🦿Xpeng showed a humanoid robot called IRON whose movement looked so human that the team literally cut it open on stage to prove it is a machine. IRON uses a bionic body with a flexible spine, synthetic muscles, and soft skin so joints and torso can twist smoothly like a person. The system has 82 degrees of freedom in total with 22 in each hand for fine finger control. Compute runs on 3 custom AI chips rated at 2,250 TOPS (Tera Operations Per Second), which is far above typical laptop neural accelerators, so it can handle vision and motion planning on the robot. The AI stack focuses on turning camera input directly into body movement without routing through text, which reduces lag and makes the gait look natural. Xpeng staged the cut-open demo at AI Day in Guangzhou this week, addressing rumors that a performer was inside by exposing internal actuators, wiring, and cooling. Company materials also mention a large physical-world model and a multi-brain control setup for dialogue, perception, and locomotion, hinting at a path from stage demos to service work. Production is targeted for 2026, so near-term tasks will be limited, but the hardware shows a serious step toward human-scale manipulation.

Rohan Paul

3,802,543 views • 10 months ago

🇨🇳 CHINA NOW HAS A TERMINATOR PATROLLING WITH POLICE IN PUBLIC In the south of China, a humanoid robot straight out of a sci-fi movie was spotted walking side by side with real armed cops. It happened in Shenzhen, where the machine, EngineAI T800, casually joined police patrol like it’s 2049 already. Yeah, they literally called it the T800, and it looks like a jacked metal soldier ready to arrest your grandma for walking too slow. This went down at “Window of the World,” a major tourist spot, and no one even blinked. Source: Shenzhen Channel

🇨🇳 CHINA NOW HAS A TERMINATOR PATROLLING WITH POLICE IN PUBLIC In the south of China, a humanoid robot straight out of a sci-fi movie was spotted walking side by side with real armed cops. It happened in Shenzhen, where the machine, EngineAI T800, casually joined police patrol like it’s 2049 already. Yeah, they literally called it the T800, and it looks like a jacked metal soldier ready to arrest your grandma for walking too slow. This went down at “Window of the World,” a major tourist spot, and no one even blinked. Source: Shenzhen Channel

Mario Nawfal

603,516 views • 8 months ago

𝗙𝗼𝗿𝗴𝗶𝗻𝗴 𝗜𝗻𝗱𝗶𝗮'𝘀 𝗙𝘂𝘁𝘂𝗿𝗲 𝗶𝗻 𝗔𝗲𝗿𝗼𝘀𝗽𝗮𝗰𝗲 & 𝗗𝗲𝗳𝗲𝗻𝗰𝗲. PTC Industries and Aerolloy Technologies mark another defining milestone with the installation and successful trials of 𝗜𝗻𝗱𝗶𝗮'𝘀 𝗹𝗮𝗿𝗴𝗲𝘀𝘁 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗢𝗽𝗲𝗻 𝗗𝗶𝗲 𝗙𝗼𝗿𝗴𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺 for critical materials. This 𝟰𝟱𝟬𝟬/𝟱𝟭𝟬𝟬𝗧 press now is operational at the Strategic Materials Technology Complex in Lucknow. This is not incremental capacity. This is a strategic capability. Engineered for precision and scale, this system enables production of large, complex forgings in 𝗧𝗶𝘁𝗮𝗻𝗶𝘂𝗺, 𝗦𝘂𝗽𝗲𝗿𝗮𝗹𝗹𝗼𝘆𝘀, and advanced high-performance alloys powering critical components that form the backbone of next-generation aeroengines and mission-critical defence platforms. With this, our ecosystem now brings together melting, casting, and forging - all in one location. No other supply chain globally offers this level of integration at this scale and precision at the same location. With this step, we do. What this unlocks: 🔹 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝗲: Building domestic strength in critical forging capabilities that India has long relied on imports for. 🔹 𝗚𝗹𝗼𝗯𝗮𝗹 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲𝗻𝗲𝘀𝘀: Meeting the exacting requirements of advanced civil and military aerospace programs worldwide. 🔹 𝗘𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝗰𝗼𝗻𝘁𝗿𝗼𝗹: From critical materials to finished components with scale, and reliability at every step. This milestone is part of a larger conviction to build, scale, and lead in high-performance materials and manufacturing. From India, for the world. Read more here:

𝗙𝗼𝗿𝗴𝗶𝗻𝗴 𝗜𝗻𝗱𝗶𝗮'𝘀 𝗙𝘂𝘁𝘂𝗿𝗲 𝗶𝗻 𝗔𝗲𝗿𝗼𝘀𝗽𝗮𝗰𝗲 & 𝗗𝗲𝗳𝗲𝗻𝗰𝗲. PTC Industries and Aerolloy Technologies mark another defining milestone with the installation and successful trials of 𝗜𝗻𝗱𝗶𝗮'𝘀 𝗹𝗮𝗿𝗴𝗲𝘀𝘁 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗢𝗽𝗲𝗻 𝗗𝗶𝗲 𝗙𝗼𝗿𝗴𝗶𝗻𝗴 𝗦𝘆𝘀𝘁𝗲𝗺 for critical materials. This 𝟰𝟱𝟬𝟬/𝟱𝟭𝟬𝟬𝗧 press now is operational at the Strategic Materials Technology Complex in Lucknow. This is not incremental capacity. This is a strategic capability. Engineered for precision and scale, this system enables production of large, complex forgings in 𝗧𝗶𝘁𝗮𝗻𝗶𝘂𝗺, 𝗦𝘂𝗽𝗲𝗿𝗮𝗹𝗹𝗼𝘆𝘀, and advanced high-performance alloys powering critical components that form the backbone of next-generation aeroengines and mission-critical defence platforms. With this, our ecosystem now brings together melting, casting, and forging - all in one location. No other supply chain globally offers this level of integration at this scale and precision at the same location. With this step, we do. What this unlocks: 🔹 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝗲: Building domestic strength in critical forging capabilities that India has long relied on imports for. 🔹 𝗚𝗹𝗼𝗯𝗮𝗹 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲𝗻𝗲𝘀𝘀: Meeting the exacting requirements of advanced civil and military aerospace programs worldwide. 🔹 𝗘𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱 𝗰𝗼𝗻𝘁𝗿𝗼𝗹: From critical materials to finished components with scale, and reliability at every step. This milestone is part of a larger conviction to build, scale, and lead in high-performance materials and manufacturing. From India, for the world. Read more here:

PTC Industries

71,410 views • 5 months ago

Google dropped another banger! They just released a comprehensive white-paper on AgentOps - the missing piece between building AI agents and actually shipping them to production. Here's the reality: Building an AI agent takes minutes. Making it production-ready? That's where 80% of the real work begins. Google's "Prototype to Production" guide tackles this exact problem. The framework has three core pillars: 1. Evaluation-Gated Deployment: No agent reaches users without passing tests. Build a "golden dataset" that validates behavior, not just functionality. This catches what unit tests miss - agents choosing wrong tools or hallucinating responses. 2. Automated CI/CD for Agents: Test in stages: pre-merge checks for fast feedback, staging for load testing, then gated production. Version everything: prompts, tools, configs, evaluation datasets. 3. Observe → Act → Evolve Loop Production isn't the finish line. Monitor through logs, traces, and metrics. Act with circuit breakers and human escalation. Evolve by turning production failures into test cases. The best part? They released the Agent Starter Pack - a template with CI/CD, Terraform deployment, and built-in observability. Helps you spin up an evaluation pipeline in minutes. The guide also talks about the two major protocols and how they can work together. ↳ MCP for tool integration ↳ A2A for agent collaboration If you're shipping agents to production, you should read this. I've shared the full white-paper in the next tweet!

Google dropped another banger! They just released a comprehensive white-paper on AgentOps - the missing piece between building AI agents and actually shipping them to production. Here's the reality: Building an AI agent takes minutes. Making it production-ready? That's where 80% of the real work begins. Google's "Prototype to Production" guide tackles this exact problem. The framework has three core pillars: 1. Evaluation-Gated Deployment: No agent reaches users without passing tests. Build a "golden dataset" that validates behavior, not just functionality. This catches what unit tests miss - agents choosing wrong tools or hallucinating responses. 2. Automated CI/CD for Agents: Test in stages: pre-merge checks for fast feedback, staging for load testing, then gated production. Version everything: prompts, tools, configs, evaluation datasets. 3. Observe → Act → Evolve Loop Production isn't the finish line. Monitor through logs, traces, and metrics. Act with circuit breakers and human escalation. Evolve by turning production failures into test cases. The best part? They released the Agent Starter Pack - a template with CI/CD, Terraform deployment, and built-in observability. Helps you spin up an evaluation pipeline in minutes. The guide also talks about the two major protocols and how they can work together. ↳ MCP for tool integration ↳ A2A for agent collaboration If you're shipping agents to production, you should read this. I've shared the full white-paper in the next tweet!

Akshay 🚀

37,187 views • 10 months ago

China now has its own “Bolt” — a robot named after sprint legend Usain Bolt. A Chinese research team has unveiled the world’s first full-size humanoid robot to reach a peak speed of 10 meters per second, setting a new global benchmark for humanoid running. Bolt runs like a body pushed to the limit. Its joints and power systems work in tight coordination, keeping it balanced even at sprint speed. Built to match the build of an adult man—1.75 meters tall and 75 kilograms—it is a life-sized system operating at the edge of physics. Compared with Usain Bolt’s iconic 9.58-second 100-meter world record, which many experts believe may stand for decades, the gap between humans and machines is narrowing fast. Chinese robots are now challenging the ceiling of human performance—much as AlphaGo once challenged Go champion Ke Jie. The breakthrough builds on earlier world-record achievements in high-speed robotic running and marks a giant leap for China in humanoid motion and control. Beyond records, Bolt also carries practical value: robots are leaving the lab and stepping into real-world settings—sports training, emergency response, and demanding industrial tasks where speed, balance and control truly matter.

China now has its own “Bolt” — a robot named after sprint legend Usain Bolt. A Chinese research team has unveiled the world’s first full-size humanoid robot to reach a peak speed of 10 meters per second, setting a new global benchmark for humanoid running. Bolt runs like a body pushed to the limit. Its joints and power systems work in tight coordination, keeping it balanced even at sprint speed. Built to match the build of an adult man—1.75 meters tall and 75 kilograms—it is a life-sized system operating at the edge of physics. Compared with Usain Bolt’s iconic 9.58-second 100-meter world record, which many experts believe may stand for decades, the gap between humans and machines is narrowing fast. Chinese robots are now challenging the ceiling of human performance—much as AlphaGo once challenged Go champion Ke Jie. The breakthrough builds on earlier world-record achievements in high-speed robotic running and marks a giant leap for China in humanoid motion and control. Beyond records, Bolt also carries practical value: robots are leaving the lab and stepping into real-world settings—sports training, emergency response, and demanding industrial tasks where speed, balance and control truly matter.

Sinical

111,438 views • 7 months ago

This work makes a humanoid robot do simple parkour moves by looking with a depth camera and choosing the right move on the fly. The big deal is that it turns lots of small human moves into long, real-time robot behavior, without hand-coding every transition or retraining for each new course. A humanoid robot is usually good at steady walking, but it often fails when it has to do fast moves like jumping up, vaulting, or rolling, and then keep going to the next obstacle. The hard part is that you cannot easily collect training data for every possible obstacle shape, distance, and mistake, so robots end up learning a few moves that only work in a narrow setup. This work starts from short clips of real human parkour moves, like stepping over, vaulting, climbing, and rolling. It uses motion matching, which is basically a smart “pick the next clip that fits best right now” search, to stitch those short clips into a long, smooth plan that looks like a human doing a whole course. Then it trains a controller with reinforcement learning (RL), which means the robot learns by trial and error to copy that plan while staying balanced and not falling. After training separate expert controllers for different moves, it compresses them into 1 controller that uses only onboard depth sensing and a simple “go this fast in this direction” command. In real tests on a Unitree G1 humanoid, it can clear multiple obstacles in a row, adapt when obstacles get moved, and climb a wall up to 1.25m.

This work makes a humanoid robot do simple parkour moves by looking with a depth camera and choosing the right move on the fly. The big deal is that it turns lots of small human moves into long, real-time robot behavior, without hand-coding every transition or retraining for each new course. A humanoid robot is usually good at steady walking, but it often fails when it has to do fast moves like jumping up, vaulting, or rolling, and then keep going to the next obstacle. The hard part is that you cannot easily collect training data for every possible obstacle shape, distance, and mistake, so robots end up learning a few moves that only work in a narrow setup. This work starts from short clips of real human parkour moves, like stepping over, vaulting, climbing, and rolling. It uses motion matching, which is basically a smart “pick the next clip that fits best right now” search, to stitch those short clips into a long, smooth plan that looks like a human doing a whole course. Then it trains a controller with reinforcement learning (RL), which means the robot learns by trial and error to copy that plan while staying balanced and not falling. After training separate expert controllers for different moves, it compresses them into 1 controller that uses only onboard depth sensing and a simple “go this fast in this direction” command. In real tests on a Unitree G1 humanoid, it can clear multiple obstacles in a row, adapt when obstacles get moved, and climb a wall up to 1.25m.

Rohan Paul

37,121 views • 6 months ago

🚀 Optimus is gearing up for MASS PRODUCTION — and it’s about to change everything. Tesla is preparing its first large-scale Optimus factory in Fremont (replacing Model S/X lines) targeting 1 million robots per year, with a second-gen line in Austin aiming for 10 million annual capacity! Gen 3 is already walking, refining its moves, and the AI brains (powered by the same tech as FSD/Robotaxi) are accelerating fast. This isn’t just a robot — it’s Tesla’s next leap toward solving labor shortages, boosting productivity, and accelerating our sustainable energy + autonomy future. Imagine helpful Optimus bots in homes, factories, and beyond, freeing humans for higher pursuits while advancing the mission. The robotics revolution is closer than ever. 🤖✨ What excites you most about Optimus — household helper, factory teammate, or something bigger? Drop your vision below! 👇 Like if you’re bullish on Tesla’s multi-product future | Repost to spread the hype | Follow for daily Tesla energy 🔥 #Tesla #Optimus #RobotRevolution #FSD #SustainableFuture #Cybertruck

🚀 Optimus is gearing up for MASS PRODUCTION — and it’s about to change everything. Tesla is preparing its first large-scale Optimus factory in Fremont (replacing Model S/X lines) targeting 1 million robots per year, with a second-gen line in Austin aiming for 10 million annual capacity! Gen 3 is already walking, refining its moves, and the AI brains (powered by the same tech as FSD/Robotaxi) are accelerating fast. This isn’t just a robot — it’s Tesla’s next leap toward solving labor shortages, boosting productivity, and accelerating our sustainable energy + autonomy future. Imagine helpful Optimus bots in homes, factories, and beyond, freeing humans for higher pursuits while advancing the mission. The robotics revolution is closer than ever. 🤖✨ What excites you most about Optimus — household helper, factory teammate, or something bigger? Drop your vision below! 👇 Like if you’re bullish on Tesla’s multi-product future | Repost to spread the hype | Follow for daily Tesla energy 🔥 #Tesla #Optimus #RobotRevolution #FSD #SustainableFuture #Cybertruck

Kendall

15,521 views • 3 months ago

🚨 BREAKING: Walden Robotics has just come out of stealth with $300 million in funding and a $1.1 billion valuation. Another unicorn in the robotics space. 🦄 Just 6 months after incubation. The company was spun out of Toyota's robotics research lab by co-founder Russ Tedrake, a former Toyota Research Institute executive and MIT professor who taught a course on robotic legs. The seed round was co-led by Deviation Capital and Toyota, with participation from: NVIDIA, Boeing, Samsung Ventures, CoreWeave Ventures and AE Ventures. The robot is already working. A pilot is live at a North American Toyota factory where a Walden humanoid is pulling eight-hour shifts alongside human workers, loading and unloading car parts, cleaning machinery, kitting for assembly. A shift. Every day. Walden builds its own hardware, software and AI models, designed to continuously learn and improve in real production environments. Tedrake's words on the opportunity are worth noting: "Everyone recognises the magnitude of the opportunity and the technology feels ready, but success is not assured. You have to think through the business case, the unit economics, and how to marry the best of manufacturing and logistics with disruptive AI technology." Rare honesty in a space full of hype. The race to own that market is accelerating every single week. 🤖 Great story by Bloomberg here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

🚨 BREAKING: Walden Robotics has just come out of stealth with $300 million in funding and a $1.1 billion valuation. Another unicorn in the robotics space. 🦄 Just 6 months after incubation. The company was spun out of Toyota's robotics research lab by co-founder Russ Tedrake, a former Toyota Research Institute executive and MIT professor who taught a course on robotic legs. The seed round was co-led by Deviation Capital and Toyota, with participation from: NVIDIA, Boeing, Samsung Ventures, CoreWeave Ventures and AE Ventures. The robot is already working. A pilot is live at a North American Toyota factory where a Walden humanoid is pulling eight-hour shifts alongside human workers, loading and unloading car parts, cleaning machinery, kitting for assembly. A shift. Every day. Walden builds its own hardware, software and AI models, designed to continuously learn and improve in real production environments. Tedrake's words on the opportunity are worth noting: "Everyone recognises the magnitude of the opportunity and the technology feels ready, but success is not assured. You have to think through the business case, the unit economics, and how to marry the best of manufacturing and logistics with disruptive AI technology." Rare honesty in a space full of hype. The race to own that market is accelerating every single week. 🤖 Great story by Bloomberg here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

76,114 views • 2 months ago

A monowheel security robot from Estonia! 🇪🇪 Rollo Robotics just raised €3.7M pre-seed led by FoodLabs and PROTOTYPE to bring the world's first stable autonomous monowheel robot to market. Founded by Arno Kütt (the mind behind Cleveron) and Sander Sebastian Agur, this Estonian startup has cracked what they call the "stability paradox" of the monowheel. Instead of clunky multi-wheeled platforms, Rollo uses high-frequency sensor fusion and proprietary balance control to create a slim, agile robot that navigates tight urban spaces and industrial corridors where traditional robots simply can't fit. The application? Autonomous security patrolling. With hybrid threats to physical infrastructure growing, the demand for scalable robotic security is massive. The funding will go toward two things: hardening the tech for extreme weather and high-traffic environments, and scaling production to meet demand from early pilot programs. 💰 P.S. Monowheels have been sci-fi for decades. Excited to see if Rollo can make them practical at scale. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

A monowheel security robot from Estonia! 🇪🇪 Rollo Robotics just raised €3.7M pre-seed led by FoodLabs and PROTOTYPE to bring the world's first stable autonomous monowheel robot to market. Founded by Arno Kütt (the mind behind Cleveron) and Sander Sebastian Agur, this Estonian startup has cracked what they call the "stability paradox" of the monowheel. Instead of clunky multi-wheeled platforms, Rollo uses high-frequency sensor fusion and proprietary balance control to create a slim, agile robot that navigates tight urban spaces and industrial corridors where traditional robots simply can't fit. The application? Autonomous security patrolling. With hybrid threats to physical infrastructure growing, the demand for scalable robotic security is massive. The funding will go toward two things: hardening the tech for extreme weather and high-traffic environments, and scaling production to meet demand from early pilot programs. 💰 P.S. Monowheels have been sci-fi for decades. Excited to see if Rollo can make them practical at scale. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

18,863 views • 8 months ago