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5-axis 3D printing is pushing additive manufacturing beyond traditional limits. 🤯 This helical coil was produced using the 5-axis system developed by Generative Machine Company, with Aibuild software generating the synchronized multi-axis toolpath. The machine and software work together to dynamically control the print path, layer height and speed,...

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Engineers: “This is a breakthrough in soft robotics.” Twitter: “Bro built an AI vibrator.” 🤦‍♂️ Researchers at the University of Southern Denmark created a soft robot that moves by inflating and contracting its body like a worm. Jokes aside… robots like this could actually be useful for rescue missions and environments where traditional robots fail. But let’s be honest: you already know what most comment sections are going to talk about 💀 🎥 Media: SDU Soft Robotics ⚠️ 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.
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Engineers: “This is a breakthrough in soft robotics.” Twitter: “Bro built an AI vibrator.” 🤦‍♂️ Researchers at the University of Southern Denmark created a soft robot that moves by inflating and contracting its body like a worm. Jokes aside… robots like this could actually be useful for rescue missions and environments where traditional robots fail. But let’s be honest: you already know what most comment sections are going to talk about 💀 🎥 Media: SDU Soft Robotics ⚠️ 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.

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This is the kind of project that quietly changes an industry. Instead of using traditional slicers, this creator built an app that converts hand-drawn curves directly into printable G-code for spiral vase mode prints. App → G-code → Print. - No complicated workflow. - No heavy setup. - Just turning ideas into physical objects almost instantly. The interesting part isn’t just the print quality. It’s how tools are becoming so simple that more people can create complex things without needing advanced technical knowledge. Would tools like this make 3D printing finally mainstream? 🎥 Media: ( Instagram ) ⚠️ 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.
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This is the kind of project that quietly changes an industry. Instead of using traditional slicers, this creator built an app that converts hand-drawn curves directly into printable G-code for spiral vase mode prints. App → G-code → Print. - No complicated workflow. - No heavy setup. - Just turning ideas into physical objects almost instantly. The interesting part isn’t just the print quality. It’s how tools are becoming so simple that more people can create complex things without needing advanced technical knowledge. Would tools like this make 3D printing finally mainstream? 🎥 Media: ( Instagram ) ⚠️ 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.

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Almost every robot you see... runs on this equation. Not AI. Not machine learning. PID. For over 100 years, this simple control algorithm has been quietly keeping robots balanced, drones stable, industrial machines precise, and even rockets on course. Most people never hear about it. Yet without PID, many of today's robots wouldn't even stand upright. If you could only learn ONE control algorithm in robotics... this would be it. What's the most impressive application of PID you've seen? 🎥 Media: medcorreia ( Instagram ) ⚠️ 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.
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Almost every robot you see... runs on this equation. Not AI. Not machine learning. PID. For over 100 years, this simple control algorithm has been quietly keeping robots balanced, drones stable, industrial machines precise, and even rockets on course. Most people never hear about it. Yet without PID, many of today's robots wouldn't even stand upright. If you could only learn ONE control algorithm in robotics... this would be it. What's the most impressive application of PID you've seen? 🎥 Media: medcorreia ( Instagram ) ⚠️ 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.

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China is scaling humanoid robotics at an insane speed. Super realistic robots from Ex-Robots are now reportedly entering mass production 🤖 - Not prototypes. - Not lab experiments. - Actual production. The biggest shift happening in robotics isn’t just intelligence anymore. It’s making robots look and behave socially acceptable around humans. And honestly… we’re reaching the point where some people may not immediately realize they’re talking to a robot. Exciting future or uncomfortable future? Media : Ex-Robots ⚠️ 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.
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China is scaling humanoid robotics at an insane speed. Super realistic robots from Ex-Robots are now reportedly entering mass production 🤖 - Not prototypes. - Not lab experiments. - Actual production. The biggest shift happening in robotics isn’t just intelligence anymore. It’s making robots look and behave socially acceptable around humans. And honestly… we’re reaching the point where some people may not immediately realize they’re talking to a robot. Exciting future or uncomfortable future? Media : Ex-Robots ⚠️ 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.

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This drone doesn’t just carry objects it grabs them. 🤯 Meet Ring-Rotor, a retractable quadrotor developed by researchers at Zhejiang University. Instead of using a robotic arm, the drone changes its shape and surrounds the object, allowing it to grasp and transport different payloads in mid-air. The frame can also shrink by about 31%, helping it pass through tighter spaces. No hook. No cable. No external gripper. The drone itself becomes the gripper. 🎥 Media: Yuze Wu , Fei Gao & Zhejiang University ⚠️ 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. #Robotics #DroneTechnology #AerialRobotics #AerialManipulation #Automation #Engineering #Innovation #FutureTech
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This drone doesn’t just carry objects it grabs them. 🤯 Meet Ring-Rotor, a retractable quadrotor developed by researchers at Zhejiang University. Instead of using a robotic arm, the drone changes its shape and surrounds the object, allowing it to grasp and transport different payloads in mid-air. The frame can also shrink by about 31%, helping it pass through tighter spaces. No hook. No cable. No external gripper. The drone itself becomes the gripper. 🎥 Media: Yuze Wu , Fei Gao & Zhejiang University ⚠️ 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. #Robotics #DroneTechnology #AerialRobotics #AerialManipulation #Automation #Engineering #Innovation #FutureTech

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Researchers at Columbia University have developed modular robots that can adapt, repair, and even rebuild themselves using a concept called robot metabolism. 🤖 Instead of remaining fixed, these robots can detach, reconnect, and reorganize their own structure based on the task or environment. If one part is damaged, the system can replace or rearrange itself rather than stopping completely. This could reshape the future of disaster response, industrial automation, and even space exploration. The idea of robots that evolve instead of wear out is becoming more than science fiction. What real-world application do you think will benefit most from this technology? 🎥 Media: Columbia University ⚠️ 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.
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Researchers at Columbia University have developed modular robots that can adapt, repair, and even rebuild themselves using a concept called robot metabolism. 🤖 Instead of remaining fixed, these robots can detach, reconnect, and reorganize their own structure based on the task or environment. If one part is damaged, the system can replace or rearrange itself rather than stopping completely. This could reshape the future of disaster response, industrial automation, and even space exploration. The idea of robots that evolve instead of wear out is becoming more than science fiction. What real-world application do you think will benefit most from this technology? 🎥 Media: Columbia University ⚠️ 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

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5-Axis CNC machining of turbocharger impellers sits in the same league as aerospace manufacturing, precision engineering pushed to physical limits. These machines run with positional accuracy in the 1-5 micron range, spindle speeds of 20,000-40,000 RPM, and continuous 5-axis interpolation to carve complex blade geometry without collision, vibration, or thermal drift during cutting of nickel alloys and titanium. A production-grade 5-axis system for impellers typically costs $300,000 to $3 million+ The real constraint is not motion, but stability, suppressing chatter, tool deflection, and microscopic surface defects that would quietly destroy efficiency at 100,000+ RPM operating cycles. Without this class of machining, modern turbocharged engines, high-efficiency industrial compressors, and compact propulsion systems simply would not exist.
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5-Axis CNC machining of turbocharger impellers sits in the same league as aerospace manufacturing, precision engineering pushed to physical limits. These machines run with positional accuracy in the 1-5 micron range, spindle speeds of 20,000-40,000 RPM, and continuous 5-axis interpolation to carve complex blade geometry without collision, vibration, or thermal drift during cutting of nickel alloys and titanium. A production-grade 5-axis system for impellers typically costs $300,000 to $3 million+ The real constraint is not motion, but stability, suppressing chatter, tool deflection, and microscopic surface defects that would quietly destroy efficiency at 100,000+ RPM operating cycles. Without this class of machining, modern turbocharged engines, high-efficiency industrial compressors, and compact propulsion systems simply would not exist.

Ammanichanda

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A lot of you are thinking that the spring which we will supply to Prakash Dadlani will be produced at the speed of 1304 ppm. That’s not true. All springs are not made on one kind of machine. The CNC machine we built that produces springs up to 1304 ppm manufactures compression springs. Whereas, the springs for Prakash bhai will be made on one of our 12-axis CNC wire forming machine. And on this the speed is much slower but it has flexibility to produce a number of different kinds of springs and wire forms. The design, type, materials, wire diameter and profile, features and precision of the springs defines what kind of machine will be used. It’s not one machine that does it all. This video is of that springs being manufactured on our other CNC machine. Also, the operator is setting the spring up that is why he is using his hands. Once it’s in production, there’s a crate underneath the machine for the springs.
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A lot of you are thinking that the spring which we will supply to Prakash Dadlani will be produced at the speed of 1304 ppm. That’s not true. All springs are not made on one kind of machine. The CNC machine we built that produces springs up to 1304 ppm manufactures compression springs. Whereas, the springs for Prakash bhai will be made on one of our 12-axis CNC wire forming machine. And on this the speed is much slower but it has flexibility to produce a number of different kinds of springs and wire forms. The design, type, materials, wire diameter and profile, features and precision of the springs defines what kind of machine will be used. It’s not one machine that does it all. This video is of that springs being manufactured on our other CNC machine. Also, the operator is setting the spring up that is why he is using his hands. Once it’s in production, there’s a crate underneath the machine for the springs.

Vishakh Ranotra

26,337 Aufrufe • vor 6 Monaten

🚨 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.
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🚨 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 Aufrufe • vor 2 Monaten

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
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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

38,188 Aufrufe • vor 28 Tagen

🚨 CHINESE SCIENTISTS JUST INVENTED 3D PRINTING THAT CREATES OBJECTS IN 0.6 SECONDS USING ONLY LIGHT. Researchers at Tsinghua University have developed a new method called DISH (Digital Incoherent Synthesis of Holographic light fields) that can print complex millimeter-scale objects almost instantly. Instead of slowly building layer by layer, the system fires thousands of precisely patterned light images from multiple angles into a still vat of liquid resin. Where the light overlaps, the resin instantly hardens into a solid 3D object. The entire process takes just 0.6 seconds. Why this matters: • It’s currently the fastest volumetric 3D printing method ever demonstrated • Achieves extremely fine detail features thinner than a human hair • The resin stays completely still, so there’s no vibration or distortion • It can work with watery (low-viscosity) resins, making it suitable for biological applications • The team has already printed complex structures like blood vessel-like tubes and even a tiny bust of a historical figure The deeper implication: Traditional 3D printing has always been limited by speed and the need to move either the print head or the resin. This approach removes both constraints by using light itself as the sculptor. Because it can print directly into still liquid (and potentially onto living tissue), it opens new possibilities in bioprinting, medical devices, and rapid manufacturing. If the technology can be scaled beyond millimeter sizes, it could fundamentally change how we think about making physical objects turning “print” from a slow process into something closer to instantaneous fabrication. We’re moving from “layer by layer” to “all at once.” How do you think instant volumetric 3D printing like this could change medicine, manufacturing, or everyday life if it becomes widely available? Follow for more frontier manufacturing and materials science breakthroughs.
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🚨 CHINESE SCIENTISTS JUST INVENTED 3D PRINTING THAT CREATES OBJECTS IN 0.6 SECONDS USING ONLY LIGHT. Researchers at Tsinghua University have developed a new method called DISH (Digital Incoherent Synthesis of Holographic light fields) that can print complex millimeter-scale objects almost instantly. Instead of slowly building layer by layer, the system fires thousands of precisely patterned light images from multiple angles into a still vat of liquid resin. Where the light overlaps, the resin instantly hardens into a solid 3D object. The entire process takes just 0.6 seconds. Why this matters: • It’s currently the fastest volumetric 3D printing method ever demonstrated • Achieves extremely fine detail features thinner than a human hair • The resin stays completely still, so there’s no vibration or distortion • It can work with watery (low-viscosity) resins, making it suitable for biological applications • The team has already printed complex structures like blood vessel-like tubes and even a tiny bust of a historical figure The deeper implication: Traditional 3D printing has always been limited by speed and the need to move either the print head or the resin. This approach removes both constraints by using light itself as the sculptor. Because it can print directly into still liquid (and potentially onto living tissue), it opens new possibilities in bioprinting, medical devices, and rapid manufacturing. If the technology can be scaled beyond millimeter sizes, it could fundamentally change how we think about making physical objects turning “print” from a slow process into something closer to instantaneous fabrication. We’re moving from “layer by layer” to “all at once.” How do you think instant volumetric 3D printing like this could change medicine, manufacturing, or everyday life if it becomes widely available? Follow for more frontier manufacturing and materials science breakthroughs.

TheNewPhysics

347,458 Aufrufe • vor 2 Monaten

THIS 20-YEAR-OLD GIRL BROKE DOWN 5 COMPANIES IN 3D PRINTING AND FOUND WHERE THE MONEY ACTUALLY IS 3D printing looks like the business of the future, with hundreds of millions in investment swirling around it. But look closely at the ones who actually made money, and the picture turns out unexpected Every company made millions, but none of them did it on the printing itself. The reason is simple: a printer today is ordered from a catalog, and files copy for free, so anyone can replicate the printing Since the machine is easy to copy, the money shifts to what can't be. Each company has its own niche: > ICON: printing is 1 of 7 phases, the rest is finishing and engineering > Firestorm: prints where a supply chain physically can't reach > Revo: years of work on the salmon recipe, not the extruder itself > Replasia: the implant is in trials, but the measurements already sell > Alquist: a single corporate client ordered 200 buildings It works like this: first you find your niche, whether it's a client with repeat orders, a rare material or a place with no competition. And only then do you buy the printer Do it the other way and buy the machine first, and you're left competing on price with a factory and losing. The printer is just a tool, the money comes from everything built around it
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THIS 20-YEAR-OLD GIRL BROKE DOWN 5 COMPANIES IN 3D PRINTING AND FOUND WHERE THE MONEY ACTUALLY IS 3D printing looks like the business of the future, with hundreds of millions in investment swirling around it. But look closely at the ones who actually made money, and the picture turns out unexpected Every company made millions, but none of them did it on the printing itself. The reason is simple: a printer today is ordered from a catalog, and files copy for free, so anyone can replicate the printing Since the machine is easy to copy, the money shifts to what can't be. Each company has its own niche: > ICON: printing is 1 of 7 phases, the rest is finishing and engineering > Firestorm: prints where a supply chain physically can't reach > Revo: years of work on the salmon recipe, not the extruder itself > Replasia: the implant is in trials, but the measurements already sell > Alquist: a single corporate client ordered 200 buildings It works like this: first you find your niche, whether it's a client with repeat orders, a rare material or a place with no competition. And only then do you buy the printer Do it the other way and buy the machine first, and you're left competing on price with a factory and losing. The printer is just a tool, the money comes from everything built around it

Mikadzyki🌙

14,499 Aufrufe • vor 1 Monat

Polymorphic moulding: a manufacturing method that forms parts using a grid of computer-controlled pins: Each pin can move up or down independently, so together they shape a surface that acts like a custom mould. Instead of building a fixed mould for every product, the machine quickly repositions the pins to match a new digital model. This means a mould can be created in minutes, used, and then reshaped again for the next design. Because the hardware stays the same and only its configuration changes: > no permanent tooling is needed > very little material is wasted > setup time between products is minimal The system essentially turns mould making into a programmable process. Engineers send a design file, the pins form the mould geometry, and the material is cast or formed inside it. Especially useful for rapid prototyping and customised manufacturing, where many different shapes must be produced in small quantities without rebuilding tools each time. Credit: ---- Weekly robotics and AI insights. Subscribe free:
0:14

Polymorphic moulding: a manufacturing method that forms parts using a grid of computer-controlled pins: Each pin can move up or down independently, so together they shape a surface that acts like a custom mould. Instead of building a fixed mould for every product, the machine quickly repositions the pins to match a new digital model. This means a mould can be created in minutes, used, and then reshaped again for the next design. Because the hardware stays the same and only its configuration changes: > no permanent tooling is needed > very little material is wasted > setup time between products is minimal The system essentially turns mould making into a programmable process. Engineers send a design file, the pins form the mould geometry, and the material is cast or formed inside it. Especially useful for rapid prototyping and customised manufacturing, where many different shapes must be produced in small quantities without rebuilding tools each time. Credit: ---- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

38,234 Aufrufe • vor 6 Monaten

AI has had exactly two scaling axes that worked so far, and the second one is starting to look finite too the first one was pretraining: with scaling parameters and data, we got world knowledge (i.e. ChatGPT had read enough to know things), but it started saturating a while ago the second one was RL, and people had been doing RL the whole time before that: RLHF is RL but it never scaled far because it was trying to control the exact output, which tokens come out, how the text reads, but you can only push that so far before you’re just polishing RLVR dropped that constraint: giving the model a task, then checking whether the final answer is right, and ignoring everything in between -- so the model does whatever it wants in the middle and only the endpoint gets graded, and that’s much closer to actual RL and it’s what bought us planning and reasoning (arguably, tool use sits around 2.5 on this list -- while useful, it's not a different kind of thing) so one axis gave knowledge, the other gave reasoning, and both of them are one model working alone the next axis is how many models you can get working on the same problem, which is a different kind of axis than the previous two we know that multi-agent RL has always been the harder problem: I spent years in that literature and the gap between single-agent and multi-agent is definitely not incremental -- it’s a whole different class of difficulty! which is also why the derivatives are steep at the start, nobody has picked the easy wins yet... and the thing that gates this multi-agent coordination is communication: models can only coordinate as well as they can exchange information, and right now they do that by writing sentences to each other imagine what could we possibly achieve if we properly open that third axis development by letting models to exchange information in their native "language" without loosing any computational data that they produce during inference
0:14

AI has had exactly two scaling axes that worked so far, and the second one is starting to look finite too the first one was pretraining: with scaling parameters and data, we got world knowledge (i.e. ChatGPT had read enough to know things), but it started saturating a while ago the second one was RL, and people had been doing RL the whole time before that: RLHF is RL but it never scaled far because it was trying to control the exact output, which tokens come out, how the text reads, but you can only push that so far before you’re just polishing RLVR dropped that constraint: giving the model a task, then checking whether the final answer is right, and ignoring everything in between -- so the model does whatever it wants in the middle and only the endpoint gets graded, and that’s much closer to actual RL and it’s what bought us planning and reasoning (arguably, tool use sits around 2.5 on this list -- while useful, it's not a different kind of thing) so one axis gave knowledge, the other gave reasoning, and both of them are one model working alone the next axis is how many models you can get working on the same problem, which is a different kind of axis than the previous two we know that multi-agent RL has always been the harder problem: I spent years in that literature and the gap between single-agent and multi-agent is definitely not incremental -- it’s a whole different class of difficulty! which is also why the derivatives are steep at the start, nobody has picked the easy wins yet... and the thing that gates this multi-agent coordination is communication: models can only coordinate as well as they can exchange information, and right now they do that by writing sentences to each other imagine what could we possibly achieve if we properly open that third axis development by letting models to exchange information in their native "language" without loosing any computational data that they produce during inference

Sasha Malysheva

12,177 Aufrufe • vor 1 Monat

A metal origami! 🪭 This method is called Hyperbolic Metal Forming and is hypnotizing to watch. Instead of shaping metal with slow mechanical force, HMF uses controlled shockwaves to form complex geometries at extreme speed, often without the need for heavy dies or post-processing. The result is stronger, lighter parts with shapes that are almost impossible using traditional stamping. That’s why you see it popping up in aerospace, automotive structures, and defense components. Think of it like metal origami, but driven by high-energy pulses instead of presses. A small reminder that some things in manufacturing come from physics, not just automation. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:18

A metal origami! 🪭 This method is called Hyperbolic Metal Forming and is hypnotizing to watch. Instead of shaping metal with slow mechanical force, HMF uses controlled shockwaves to form complex geometries at extreme speed, often without the need for heavy dies or post-processing. The result is stronger, lighter parts with shapes that are almost impossible using traditional stamping. That’s why you see it popping up in aerospace, automotive structures, and defense components. Think of it like metal origami, but driven by high-energy pulses instead of presses. A small reminder that some things in manufacturing come from physics, not just automation. ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

567,473 Aufrufe • vor 9 Monaten

FIVE LAYERS OF AGENT ENGINEERING, EACH ONE WRAPS THE ONE BELOW IT. IF YOU SKIP LAYER 2, YOUR LAYER 5 WILL LOOK BROKEN WHEN IT IS ACTUALLY JUST STANDING ON NOTHING. for weeks i debated harness vs loop vs graph like they were competing choices. then a stack diagram made the shape obvious. they are not choices. they are floors. 01 | prompt engineering. the message. unit of work: one input. inputs are role, instructions, examples, format. output is a single raw response. 02 | context engineering. the memory. unit of work: what stays in the window. a curator selects, compresses, and drops from query, docs, memory, prior turns, and tool outputs before the prompt runs. 03 | harness engineering. the machine. unit of work: the machine itself. gather (context + prompt) → LLM → tools or sub-agents → verifier → final response. the article calls this the operating environment. 04 | loop engineering. the system. unit of work: the run. goal + success criteria + max iterations + budget + completion check wrap around one harness pass. failed pass appends results to context and retries. 05 | graph engineering. the topology. unit of work: the graph run. goal + nodes + edges + state schema. graph routes to agent nodes, tool nodes, or human approval. a reviewer node with a different model and fresh context checks the final answer. the wrapping is the whole point. layer 5 assumes layer 4 works. layer 4 assumes layer 3 works. skip layer 2 and layer 3's verifier keeps failing without a clear reason. this is why swapping the model is a one-day project and swapping the stack is a quarter. the model is the commodity. the five layers around it are the engineering. full three-layer breakdown of the top of the stack (harness, loop, graph) in the post below.
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FIVE LAYERS OF AGENT ENGINEERING, EACH ONE WRAPS THE ONE BELOW IT. IF YOU SKIP LAYER 2, YOUR LAYER 5 WILL LOOK BROKEN WHEN IT IS ACTUALLY JUST STANDING ON NOTHING. for weeks i debated harness vs loop vs graph like they were competing choices. then a stack diagram made the shape obvious. they are not choices. they are floors. 01 | prompt engineering. the message. unit of work: one input. inputs are role, instructions, examples, format. output is a single raw response. 02 | context engineering. the memory. unit of work: what stays in the window. a curator selects, compresses, and drops from query, docs, memory, prior turns, and tool outputs before the prompt runs. 03 | harness engineering. the machine. unit of work: the machine itself. gather (context + prompt) → LLM → tools or sub-agents → verifier → final response. the article calls this the operating environment. 04 | loop engineering. the system. unit of work: the run. goal + success criteria + max iterations + budget + completion check wrap around one harness pass. failed pass appends results to context and retries. 05 | graph engineering. the topology. unit of work: the graph run. goal + nodes + edges + state schema. graph routes to agent nodes, tool nodes, or human approval. a reviewer node with a different model and fresh context checks the final answer. the wrapping is the whole point. layer 5 assumes layer 4 works. layer 4 assumes layer 3 works. skip layer 2 and layer 3's verifier keeps failing without a clear reason. this is why swapping the model is a one-day project and swapping the stack is a quarter. the model is the commodity. the five layers around it are the engineering. full three-layer breakdown of the top of the stack (harness, loop, graph) in the post below.

kocer

30,675 Aufrufe • vor 11 Tagen

U.S. company Powerus has unveiled the Matrix Fold, a modular and foldable FPV drone reportedly selected for the Pentagon’s Drone Dominance program. The 12-inch platform is designed to fold into a compact form that can reportedly fit into a backpack and be deployed within seconds. Its 3D-printed construction is intended to allow individual components to be replaced in the field, with printing files reportedly supplied for manufacturing replacement parts. According to Powerus, the Matrix Fold has a maximum speed of 242 km/h, a payload capacity of up to 6.8 kg and an endurance of up to 35 minutes. The system features a modular architecture compatible with the company’s Matrix 5, 7, 10 and F platforms. Tool-free maintenance and rapid payload changes are also reportedly supported. Powerus states that the Matrix Fold is NDAA-compliant and Blue UAS certified, with its supply chain under company control. In May 2026, the Matrix Fold was reportedly selected for the second phase of the Pentagon’s Drone Dominance program, described as having a value of approximately $1 billion. The program is intended to support the procurement of tens of thousands of low-cost, expendable drones and expand U.S. domestic production capacity. Serial production is reportedly planned to follow the program’s next phase. #USA #Powerus #MatrixFold #FPV #FPVDrone #DroneDominance #Pentagon #UAV #DroneWarfare #3DPrinting #BlueUAS #NDAA
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U.S. company Powerus has unveiled the Matrix Fold, a modular and foldable FPV drone reportedly selected for the Pentagon’s Drone Dominance program. The 12-inch platform is designed to fold into a compact form that can reportedly fit into a backpack and be deployed within seconds. Its 3D-printed construction is intended to allow individual components to be replaced in the field, with printing files reportedly supplied for manufacturing replacement parts. According to Powerus, the Matrix Fold has a maximum speed of 242 km/h, a payload capacity of up to 6.8 kg and an endurance of up to 35 minutes. The system features a modular architecture compatible with the company’s Matrix 5, 7, 10 and F platforms. Tool-free maintenance and rapid payload changes are also reportedly supported. Powerus states that the Matrix Fold is NDAA-compliant and Blue UAS certified, with its supply chain under company control. In May 2026, the Matrix Fold was reportedly selected for the second phase of the Pentagon’s Drone Dominance program, described as having a value of approximately $1 billion. The program is intended to support the procurement of tens of thousands of low-cost, expendable drones and expand U.S. domestic production capacity. Serial production is reportedly planned to follow the program’s next phase. #USA #Powerus #MatrixFold #FPV #FPVDrone #DroneDominance #Pentagon #UAV #DroneWarfare #3DPrinting #BlueUAS #NDAA

Drone Wars

52,011 Aufrufe • vor 3 Tagen

🇺🇦🇪🇸 A BMP-1/2 infantry fighting vehicle equipped with the Guardian 30 combat module produced by the Spanish company Escribano Mechanical & Engineering has been spotted for the first time in Ukrainian service. 🔻 The Guardian 30 is a remotely controlled combat module armed with a 30mm automatic cannon and a coaxial 7.62mm machine gun. It is equipped with a modern fire control and targeting system. 🔻 For reference: Negotiations between Ukraine and the Spanish company began in May 2025. One of the discussed issues was the localization of production of Guardian 30 combat modules in Ukraine. This upgrade represents an important step in modernizing Ukraine’s large fleet of Soviet-era BMP vehicles. The installation of the advanced Spanish Guardian 30 module significantly increases the vehicle’s firepower and situational awareness. The talks on local production also show Ukraine’s long-term strategy to reduce dependence on foreign supplies and develop its own defense industry. Video is generated by grok AI
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🇺🇦🇪🇸 A BMP-1/2 infantry fighting vehicle equipped with the Guardian 30 combat module produced by the Spanish company Escribano Mechanical & Engineering has been spotted for the first time in Ukrainian service. 🔻 The Guardian 30 is a remotely controlled combat module armed with a 30mm automatic cannon and a coaxial 7.62mm machine gun. It is equipped with a modern fire control and targeting system. 🔻 For reference: Negotiations between Ukraine and the Spanish company began in May 2025. One of the discussed issues was the localization of production of Guardian 30 combat modules in Ukraine. This upgrade represents an important step in modernizing Ukraine’s large fleet of Soviet-era BMP vehicles. The installation of the advanced Spanish Guardian 30 module significantly increases the vehicle’s firepower and situational awareness. The talks on local production also show Ukraine’s long-term strategy to reduce dependence on foreign supplies and develop its own defense industry. Video is generated by grok AI

NSTRIKE

34,049 Aufrufe • vor 3 Monaten

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.
0:12

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 Aufrufe • vor 7 Monaten