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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...

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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.

CTO ROBOTICS Media

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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.

CTO ROBOTICS Media

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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

3,692,426 Aufrufe • vor 2 Monaten

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

CTO ROBOTICS Media

11,680 Aufrufe • vor 18 Tagen

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.

CTO ROBOTICS Media

132,290 Aufrufe • vor 3 Monaten

I’ve been eyeing this robotics platform by Vicarius Surgical for a long time and I am vi-curious to see what it can do. I like that the engineers/designers solved the surgical robotics problem in a different way. I wonder how strong it is and does it scale
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I’ve been eyeing this robotics platform by Vicarius Surgical for a long time and I am vi-curious to see what it can do. I like that the engineers/designers solved the surgical robotics problem in a different way. I wonder how strong it is and does it scale

Jonathan DeLong, MD

112,338 Aufrufe • vor 3 Jahren

Rare-event discovery for robots training is what we’ve been working on lately How would a robot react to an unusual event? What if a firefighter drone won’t be able to choke a fire (like on the video below)? Robo-doctors use cases? How to mass-produce these situations to train robots to see & react the best way? I think that open-sourced, world models like LTX can become the solution for such training process. And they might become the differentiator for the future of robotics. Of course, I’m not an expert in robotics and ML, but this topic makes me curious - and I’m curious about your thoughts
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Rare-event discovery for robots training is what we’ve been working on lately How would a robot react to an unusual event? What if a firefighter drone won’t be able to choke a fire (like on the video below)? Robo-doctors use cases? How to mass-produce these situations to train robots to see & react the best way? I think that open-sourced, world models like LTX can become the solution for such training process. And they might become the differentiator for the future of robotics. Of course, I’m not an expert in robotics and ML, but this topic makes me curious - and I’m curious about your thoughts

AmirMušić

41,839 Aufrufe • vor 19 Tagen

Something big is happening in robotics - and it’s hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.
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Something big is happening in robotics - and it’s hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.

Pierre-Alexandre Balland

186,094 Aufrufe • vor 8 Monaten

Qualia has been selected for the Google DeepMind Robotics Program. We train embodied models that put a robot on a real manual task and make it work, on the floor, not in a demo. Foundation models and reasoning are where robotics is heading, and doing that work alongside DeepMind, who are pushing this frontier, is exactly where we want to be. If you are a company looking to see how a new generation of robots can help your manual tasks, contact us at hello@qualiastudios.dev More soon
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Qualia has been selected for the Google DeepMind Robotics Program. We train embodied models that put a robot on a real manual task and make it work, on the floor, not in a demo. Foundation models and reasoning are where robotics is heading, and doing that work alongside DeepMind, who are pushing this frontier, is exactly where we want to be. If you are a company looking to see how a new generation of robots can help your manual tasks, contact us at [email protected] More soon

Qualia

87,750 Aufrufe • vor 2 Monaten

Cornell engineers have developed a robotic collective that behaves less like a machine and more like a material that flows, reshapes, and adapts to its environment without centralized control. The system, called the Cross-Link Collective, consists of dozens of small robots that have limited mobility individually, but together exhibit coordinated and sustained motion. The research, published May 20 in Science Robotics, demonstrates a robotic system that resembles soft matter, continuously deforming and reorganizing as it moves, driven by what researchers call mechanical intelligence. Cornell Duffield College of Engineering Cornell Research & Innovation Read more:
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Cornell engineers have developed a robotic collective that behaves less like a machine and more like a material that flows, reshapes, and adapts to its environment without centralized control. The system, called the Cross-Link Collective, consists of dozens of small robots that have limited mobility individually, but together exhibit coordinated and sustained motion. The research, published May 20 in Science Robotics, demonstrates a robotic system that resembles soft matter, continuously deforming and reorganizing as it moves, driven by what researchers call mechanical intelligence. Cornell Duffield College of Engineering Cornell Research & Innovation Read more:

Cornell University

74,058 Aufrufe • vor 3 Monaten

The robotics industry is about to go through the same shift software did 10 years ago. Here's why the next billion-dollar robotics company will be built by a creator — not a corporation 👇 1/ Corporate robotics requires millions in capital, years of R&D, and a massive team just to ship a product. Creators with the right platform can prototype an idea in weeks, validate with real customers, and iterate fast. 2/ This isn't theory. It's the same pattern we saw with: GitHub → software developers App Store → mobile creators YouTube → video creators Every major platform shift minted a new class of independent builders. Robotics is next. 3/ The barrier isn't talent. There are brilliant engineers everywhere — Ohio, Lagos, Mumbai, Berlin. The barrier is access. Access to tools, infrastructure, and a platform that lets them build and monetize. 4/ That's exactly what $ROBA is building — an open platform where creators build, train, share, and monetize robotic behaviors. No corporate gatekeepers. No vendor lock-in. Just creators owning their innovations. Join the revolution today.
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The robotics industry is about to go through the same shift software did 10 years ago. Here's why the next billion-dollar robotics company will be built by a creator — not a corporation 👇 1/ Corporate robotics requires millions in capital, years of R&D, and a massive team just to ship a product. Creators with the right platform can prototype an idea in weeks, validate with real customers, and iterate fast. 2/ This isn't theory. It's the same pattern we saw with: GitHub → software developers App Store → mobile creators YouTube → video creators Every major platform shift minted a new class of independent builders. Robotics is next. 3/ The barrier isn't talent. There are brilliant engineers everywhere — Ohio, Lagos, Mumbai, Berlin. The barrier is access. Access to tools, infrastructure, and a platform that lets them build and monetize. 4/ That's exactly what $ROBA is building — an open platform where creators build, train, share, and monetize robotic behaviors. No corporate gatekeepers. No vendor lock-in. Just creators owning their innovations. Join the revolution today.

Roba Labs

15,225 Aufrufe • vor 3 Monaten

The most interesting part of this robot is not the arm. It is the gripper. Instead of pushing the whole robot faster, this setup adds speed at the end effector. The gripper itself becomes a moving axis that can accelerate independently of the arm. That changes the physics of the system. • Faster cycle times without stressing the robot structure • Less inertia to fight against • Motion where it actually matters, at the tool center point It is a reminder that many performance limits in robotics are not solved by bigger motors, but by smarter mechanics. ——- Weekly robotics and AI insights. Subscribe free:
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The most interesting part of this robot is not the arm. It is the gripper. Instead of pushing the whole robot faster, this setup adds speed at the end effector. The gripper itself becomes a moving axis that can accelerate independently of the arm. That changes the physics of the system. • Faster cycle times without stressing the robot structure • Less inertia to fight against • Motion where it actually matters, at the tool center point It is a reminder that many performance limits in robotics are not solved by bigger motors, but by smarter mechanics. ——- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

46,721 Aufrufe • vor 21 Tagen

I spent a month in Shenzhen visiting factories and robotics companies, and the contrast with the U.S. was striking. While Figure and Boston Dynamics hide their humanoids behind closed doors, Chinese companies have massive showrooms open to the public. But what really stood out wasn't just the transparency, it was how good they are at selling. Take UBTech: they've already sold 1,200 humanoid units at $200k each to factories. And here's the kicker, these robots aren't even that useful yet. They can only pick up and drop boxes at 1/10th the speed of a human, and factories still need to hire system integrators to train them for specific tasks. My theory is that these factories are terrified of getting left behind in the robotics/AI wave. They're investing in new tech not because it's ready, but because they can't afford to wait. The second surprise was the breadth of their robotics portfolio. These companies aren't just building humanoids, they're deploying service robots everywhere: restaurants, hotels, apartments. Consumer robots are cleaning houses, pools, pet waste, dishes. They're covering the entire spectrum. But the education piece shocked me most. I picked up what I thought was a high school or college robotics textbook, it was for primary school. The government mandated AI and robotics education starting in elementary school. Almost every single school in China now has AI and robotics curriculum, complete with education robots so kids can learn by building. They're creating a generation that grows up fluent in robotics and AI. China owns the supply chain and the hardware stack. But here's what I think people are missing: the race isn't just about who can build robots faster or cheaper. The U.S. advantage has always been in the layer between hardware and human, the interaction design, the software intelligence, the intuitive interfaces that make complex technology feel natural. China is building the physical infrastructure, but they're also learning fast. Every deployed service robot, every classroom full of kids building with education kits, every factory running humanoids, that's all data collection at scale. The window for the U.S. to establish its wedge is narrowing. It's not enough to be better at AI or software anymore. We need to be building the integration layer, the intelligence that makes physical AI actually useful, not just impressive in a showroom. Because right now, China isn't just manufacturing robots. They're manufacturing a robotics-native culture, and that might be the most defensible moat of all.
0:10

I spent a month in Shenzhen visiting factories and robotics companies, and the contrast with the U.S. was striking. While Figure and Boston Dynamics hide their humanoids behind closed doors, Chinese companies have massive showrooms open to the public. But what really stood out wasn't just the transparency, it was how good they are at selling. Take UBTech: they've already sold 1,200 humanoid units at $200k each to factories. And here's the kicker, these robots aren't even that useful yet. They can only pick up and drop boxes at 1/10th the speed of a human, and factories still need to hire system integrators to train them for specific tasks. My theory is that these factories are terrified of getting left behind in the robotics/AI wave. They're investing in new tech not because it's ready, but because they can't afford to wait. The second surprise was the breadth of their robotics portfolio. These companies aren't just building humanoids, they're deploying service robots everywhere: restaurants, hotels, apartments. Consumer robots are cleaning houses, pools, pet waste, dishes. They're covering the entire spectrum. But the education piece shocked me most. I picked up what I thought was a high school or college robotics textbook, it was for primary school. The government mandated AI and robotics education starting in elementary school. Almost every single school in China now has AI and robotics curriculum, complete with education robots so kids can learn by building. They're creating a generation that grows up fluent in robotics and AI. China owns the supply chain and the hardware stack. But here's what I think people are missing: the race isn't just about who can build robots faster or cheaper. The U.S. advantage has always been in the layer between hardware and human, the interaction design, the software intelligence, the intuitive interfaces that make complex technology feel natural. China is building the physical infrastructure, but they're also learning fast. Every deployed service robot, every classroom full of kids building with education kits, every factory running humanoids, that's all data collection at scale. The window for the U.S. to establish its wedge is narrowing. It's not enough to be better at AI or software anymore. We need to be building the integration layer, the intelligence that makes physical AI actually useful, not just impressive in a showroom. Because right now, China isn't just manufacturing robots. They're manufacturing a robotics-native culture, and that might be the most defensible moat of all.

Miyu Horiuchi

90,718 Aufrufe • vor 7 Monaten

The most dangerous part of a humanoid robot may be the face. UBTECH’s Walker shows how a machine can use gaze stillness and humanlike expression to create trust before proving judgment reliability or accountability. Should robots be allowed to look this human in public spaces? Putting the debate aside this is clearly a work of art. Congratulations to UBTECH for this achievement. Walker looks so refined that I may need to buy one fast before the stock runs out lol. Credit : UBTECH Robotics
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The most dangerous part of a humanoid robot may be the face. UBTECH’s Walker shows how a machine can use gaze stillness and humanlike expression to create trust before proving judgment reliability or accountability. Should robots be allowed to look this human in public spaces? Putting the debate aside this is clearly a work of art. Congratulations to UBTECH for this achievement. Walker looks so refined that I may need to buy one fast before the stock runs out lol. Credit : UBTECH Robotics

Techniahqrobot | humanoid robots

51,556 Aufrufe • vor 2 Monaten

Memo is a robot that uses AI to perform household tasks effectively. Today Sunday announced its Series B, and we’re proud to be investors. Training robots for the home is hard — the environment is messy, dynamic, and full of edge cases. So Sunday is training robots directly on real households. Founders Tony Zhao and Cheng Chi built a glove-based system that lets hundreds of contributors record everyday tasks in their own homes, creating high-fidelity demonstrations that feed directly into robot learning. Home robotics will be defined by the companies that learn fastest from real homes. Sunday is building that loop. More here: Aaref Hilaly Amanda Huang
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Memo is a robot that uses AI to perform household tasks effectively. Today Sunday announced its Series B, and we’re proud to be investors. Training robots for the home is hard — the environment is messy, dynamic, and full of edge cases. So Sunday is training robots directly on real households. Founders Tony Zhao and Cheng Chi built a glove-based system that lets hundreds of contributors record everyday tasks in their own homes, creating high-fidelity demonstrations that feed directly into robot learning. Home robotics will be defined by the companies that learn fastest from real homes. Sunday is building that loop. More here: Aaref Hilaly Amanda Huang

Bain Capital Ventures

22,002 Aufrufe • vor 5 Monaten

Check out the new interactive humanoid robot, Yogi, introduced by Cartwheel Robotics. Yogi is designed as a companion for everyday life, offering help and companionship in settings from hospitals to living rooms. It features soft silicone skin for safe touch, precision actuators for predictable movement, and simple, natural interaction. The robot continuously learns new abilities for greater utility. Cartwheel's founder, Scott LaValley, has a deep background, having developed over four humanoid systems. His expertise includes nearly a decade developing the Atlas robot at Boston Dynamics, followed by five years at Disney leading the team that created the Groot robot. This extensive, hands-on experience is key to Cartwheel Robotics' innovations.
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Check out the new interactive humanoid robot, Yogi, introduced by Cartwheel Robotics. Yogi is designed as a companion for everyday life, offering help and companionship in settings from hospitals to living rooms. It features soft silicone skin for safe touch, precision actuators for predictable movement, and simple, natural interaction. The robot continuously learns new abilities for greater utility. Cartwheel's founder, Scott LaValley, has a deep background, having developed over four humanoid systems. His expertise includes nearly a decade developing the Atlas robot at Boston Dynamics, followed by five years at Disney leading the team that created the Groot robot. This extensive, hands-on experience is key to Cartwheel Robotics' innovations.

RoboHub🤖

15,243 Aufrufe • vor 11 Monaten

Imagine you go to a store and you want to buy candy. The shopkeeper knows you're a real kid because they can see you standing right there. Now imagine you send a robot to buy candy for you. The shopkeeper looks at the robot and thinks: wait, who sent this? Is this robot allowed to buy candy? What if someone else's robot pretends to be yours and steals your candy money? That's basically what's happening with AI right now. Companies like Visa let people buy things all over the world. But now, smart computer robots (AI agents) want to buy things too. Shop around, compare prices, even pay for stuff. Visa looked at this and said: nope, not yet. Because they have no way to check if the robot is real, who it belongs to, or if it's allowed to spend that money. The problem is that all the rules we have for checking identity - showing your ID, scanning your face, typing your password - only work for humans. Robots can't do any of that. Worse, bad robots can actually copy and fake human identities really well. So Evin McMullen evin, Billions Network co-founder and CEO, says we need a new kind of ID system. One where you can prove something is true without showing all your private stuff. Like proving you're tall enough for a ride without telling anyone your exact height. That's called zero-knowledge proof. And for the robots specifically, we need something called KYA - Know Your Agent. It's like giving every robot its own ID card that says: this is who I am, this is what I'm allowed to do, and this is the human responsible for me. Until we build that, the robot economy can't really get going. Here is Evin’s Thought Leader article at Silicon Valleys Journal
0:12

Imagine you go to a store and you want to buy candy. The shopkeeper knows you're a real kid because they can see you standing right there. Now imagine you send a robot to buy candy for you. The shopkeeper looks at the robot and thinks: wait, who sent this? Is this robot allowed to buy candy? What if someone else's robot pretends to be yours and steals your candy money? That's basically what's happening with AI right now. Companies like Visa let people buy things all over the world. But now, smart computer robots (AI agents) want to buy things too. Shop around, compare prices, even pay for stuff. Visa looked at this and said: nope, not yet. Because they have no way to check if the robot is real, who it belongs to, or if it's allowed to spend that money. The problem is that all the rules we have for checking identity - showing your ID, scanning your face, typing your password - only work for humans. Robots can't do any of that. Worse, bad robots can actually copy and fake human identities really well. So Evin McMullen evin, Billions Network co-founder and CEO, says we need a new kind of ID system. One where you can prove something is true without showing all your private stuff. Like proving you're tall enough for a ride without telling anyone your exact height. That's called zero-knowledge proof. And for the robots specifically, we need something called KYA - Know Your Agent. It's like giving every robot its own ID card that says: this is who I am, this is what I'm allowed to do, and this is the human responsible for me. Until we build that, the robot economy can't really get going. Here is Evin’s Thought Leader article at Silicon Valleys Journal

Billions Network

21,775 Aufrufe • vor 6 Monaten

🚨JUST IN: PEAQ OFFERS "FINANCE APPS FOR ROBOTS" DePIN-focused blockchain peaq recently posted about 'Machine Money Markets' and the way in which they both... - Connect real robots with decentralized finance - Effectively turn them into revenue-generating financial assets Through PeaqOS ( the protocols and frameworks that allow for machine interoperability), robots and machines can carry out crucial blockchain-related tasks... ... like actively using DeFi protocols, or executing sophisticated financial strategies. But that's not all. PeaqOS further allows owners to tokenise their robots, not only making them tradable, but also allowing them to be used as collateral. Peaq also shared three clear and interesting examples of Machine Money Markets, already live in the ecosystem: (1) XMAQUINA - Structured as a DAO, XMAQUINA provides open access to some of the world's most promising early-stage robotics funding rounds. (2) Dualmint - A platform built for 'Initial Machine Offerings' where users purchase shares in machines and robots running on peaq itself. (3) Robot Money - An AI agent managed treasury, wherein machines contribute revenue which is then put to use generating additional yield.
0:16

🚨JUST IN: PEAQ OFFERS "FINANCE APPS FOR ROBOTS" DePIN-focused blockchain peaq recently posted about 'Machine Money Markets' and the way in which they both... - Connect real robots with decentralized finance - Effectively turn them into revenue-generating financial assets Through PeaqOS ( the protocols and frameworks that allow for machine interoperability), robots and machines can carry out crucial blockchain-related tasks... ... like actively using DeFi protocols, or executing sophisticated financial strategies. But that's not all. PeaqOS further allows owners to tokenise their robots, not only making them tradable, but also allowing them to be used as collateral. Peaq also shared three clear and interesting examples of Machine Money Markets, already live in the ecosystem: (1) XMAQUINA - Structured as a DAO, XMAQUINA provides open access to some of the world's most promising early-stage robotics funding rounds. (2) Dualmint - A platform built for 'Initial Machine Offerings' where users purchase shares in machines and robots running on peaq itself. (3) Robot Money - An AI agent managed treasury, wherein machines contribute revenue which is then put to use generating additional yield.

BSCN

15,129 Aufrufe • vor 4 Monaten

As a newly appointed 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗼𝗿 at Imperial College London, I'm thrilled to announce the 𝗦𝗮𝗳𝗲 𝗪𝗵𝗼𝗹𝗲-𝗯𝗼𝗱𝘆 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗟𝗮𝗯 (𝗦𝗪𝗜𝗥𝗟) at 𝗜𝗺𝗽𝗲𝗿𝗶𝗮𝗹 𝗖𝗼𝗹𝗹𝗲𝗴𝗲 𝗟𝗼𝗻𝗱𝗼𝗻. 𝗦𝗮𝗳𝗲 𝗪𝗵𝗼𝗹𝗲-𝗯𝗼𝗱𝘆 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗟𝗮𝗯 (𝗦𝗪𝗜𝗥𝗟) ( is a new research lab focused on the intersection of safety and intelligence in next-generation robotics. We're hiring exceptional PhD students who are passionate about pushing the boundaries of robot learning. 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗦𝗪𝗜𝗥𝗟 𝘂𝗻𝗶𝗾𝘂𝗲? We operate at the exciting convergence of: • Online & offline reinforcement learning • Imitation learning & human demonstrations • Sample-efficient learning methods • Whole-body and soft robotics systems We're 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝗽𝗿𝗼𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲 𝗣𝗵𝗗 𝘀𝘁𝘂𝗱𝗲𝗻𝘁𝘀 interested in: • Developing safe exploration algorithms for robotic systems • Creating sample-efficient learning methods that minimize real-world trials • Building foundation models for robotics with safety guarantees • Advancing soft robotics and compliant human-robot interaction • Bridging theory and practice in embodied AI Why now? As robots become more capable and work closer with humans, we need systems that are both intelligent enough to handle complex tasks 𝗔𝗡𝗗 safe enough for real-world deployment. Traditional approaches treat safety and intelligence as competing priorities, we believe they're synergistic. If you're a motivated researcher who wants to develop the theoretical foundations and practical algorithms for tomorrow's safe, intelligent robots, I'd love to hear from you. Want to join? Apply via
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As a newly appointed 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁 𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗼𝗿 at Imperial College London, I'm thrilled to announce the 𝗦𝗮𝗳𝗲 𝗪𝗵𝗼𝗹𝗲-𝗯𝗼𝗱𝘆 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗟𝗮𝗯 (𝗦𝗪𝗜𝗥𝗟) at 𝗜𝗺𝗽𝗲𝗿𝗶𝗮𝗹 𝗖𝗼𝗹𝗹𝗲𝗴𝗲 𝗟𝗼𝗻𝗱𝗼𝗻. 𝗦𝗮𝗳𝗲 𝗪𝗵𝗼𝗹𝗲-𝗯𝗼𝗱𝘆 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗟𝗮𝗯 (𝗦𝗪𝗜𝗥𝗟) ( is a new research lab focused on the intersection of safety and intelligence in next-generation robotics. We're hiring exceptional PhD students who are passionate about pushing the boundaries of robot learning. 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗦𝗪𝗜𝗥𝗟 𝘂𝗻𝗶𝗾𝘂𝗲? We operate at the exciting convergence of: • Online & offline reinforcement learning • Imitation learning & human demonstrations • Sample-efficient learning methods • Whole-body and soft robotics systems We're 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 𝗽𝗿𝗼𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲 𝗣𝗵𝗗 𝘀𝘁𝘂𝗱𝗲𝗻𝘁𝘀 interested in: • Developing safe exploration algorithms for robotic systems • Creating sample-efficient learning methods that minimize real-world trials • Building foundation models for robotics with safety guarantees • Advancing soft robotics and compliant human-robot interaction • Bridging theory and practice in embodied AI Why now? As robots become more capable and work closer with humans, we need systems that are both intelligent enough to handle complex tasks 𝗔𝗡𝗗 safe enough for real-world deployment. Traditional approaches treat safety and intelligence as competing priorities, we believe they're synergistic. If you're a motivated researcher who wants to develop the theoretical foundations and practical algorithms for tomorrow's safe, intelligent robots, I'd love to hear from you. Want to join? Apply via

Stephen James

16,673 Aufrufe • vor 11 Monaten

Multi-robot learning is getting a serious boost! 📚 Researchers have extended Isaac Lab to train heterogeneous multi-agent robotic policies at scale. The new framework supports high-resolution physics, GPU-accelerated simulation, and both homogeneous and heterogeneous agents working together on coordination tasks. They benchmarked different approaches (MAPPO: Multi-Agent Proximal Policy Optimization and HAPPO: Heterogeneous Agent PPO) across six challenging scenarios and showed that large-scale multi-robot training is not only feasible, but efficient. It’s an important step for real-world robotic collaboration, where teams of robots need to coordinate, split tasks, adapt roles, and interact dynamically, not just operate as identical clones. The code is open-source, and it pushes Isaac Lab closer to what robotics actually needs: scalable, physics-driven environments where many different robots can learn to work together. Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
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Multi-robot learning is getting a serious boost! 📚 Researchers have extended Isaac Lab to train heterogeneous multi-agent robotic policies at scale. The new framework supports high-resolution physics, GPU-accelerated simulation, and both homogeneous and heterogeneous agents working together on coordination tasks. They benchmarked different approaches (MAPPO: Multi-Agent Proximal Policy Optimization and HAPPO: Heterogeneous Agent PPO) across six challenging scenarios and showed that large-scale multi-robot training is not only feasible, but efficient. It’s an important step for real-world robotic collaboration, where teams of robots need to coordinate, split tasks, adapt roles, and interact dynamically, not just operate as identical clones. The code is open-source, and it pushes Isaac Lab closer to what robotics actually needs: scalable, physics-driven environments where many different robots can learn to work together. Here's the project page: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

38,997 Aufrufe • vor 9 Monaten