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Imagine these Hyper-anthropomorphic humanoid robots entering people's daily lives… (AheadForm Origin F1 at WAIC, lip-syncing approaches human-level quality.)

CyberRobo

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The founder of China's biggest robotics company Unitree is 35 year old Wang Xingxing, He says humanoid robots are at the developmental level of a ten year old child. In only 3 to 10 years, these robots can be used in all major areas of people's lives. But for what else?

The founder of China's biggest robotics company Unitree is 35 year old Wang Xingxing, He says humanoid robots are at the developmental level of a ten year old child. In only 3 to 10 years, these robots can be used in all major areas of people's lives. But for what else?

Chay Bowes

21,890 Aufrufe • vor 5 Monaten

😱 Humanoid robots just performed surgery on live animals for the first time ever At UC San Diego, two humanoid robots successfully removed gallbladders from pigs. In one procedure, a robot assisted a human surgeon. In the second, two robots operated together at the table. Important note: The robots didn’t make any independent decisions — they were fully teleoperated by real doctors. But unlike bulky traditional surgical robots, these humanoids weigh just ~30 kg, move freely around the OR, and use the exact same instruments as human surgeons. This is a major milestone. The next step? Autonomy. Once achieved, these robots could become true surgical assistants, handling routine parts of procedures without constant human control. Medicine is entering a wild new era. What do you think — exciting or slightly terrifying?

😱 Humanoid robots just performed surgery on live animals for the first time ever At UC San Diego, two humanoid robots successfully removed gallbladders from pigs. In one procedure, a robot assisted a human surgeon. In the second, two robots operated together at the table. Important note: The robots didn’t make any independent decisions — they were fully teleoperated by real doctors. But unlike bulky traditional surgical robots, these humanoids weigh just ~30 kg, move freely around the OR, and use the exact same instruments as human surgeons. This is a major milestone. The next step? Autonomy. Once achieved, these robots could become true surgical assistants, handling routine parts of procedures without constant human control. Medicine is entering a wild new era. What do you think — exciting or slightly terrifying?

NEXTA

52,220 Aufrufe • vor 1 Monat

🚨 This viral bionic humanoid robot company just raised hundreds of millions RMB in funding ,and it may have finally crossed the Uncanny Valley AheadForm, the startup behind those ultra-realistic face robots that have racked up hundreds of millions of views across social media, just closed a massive A1 round. This new funding will accelerate bringing these wildly popular humanoid robots into everyday life. Worth noting: Founder Yuhang Hu's latest paper on realistic lip motions for humanoid face robots has landed on the cover of Science Robotics (Jan 2026 issue). Using self-supervised AI, their robots now generate incredibly natural, continuous lip sync,supporting multiple languages, different speaking speeds, emotions, and even singing. Powered by soft silicone skin and 10+ DoF actuators, gone are the stiff puppet faces. This marks a major leap toward truly empathetic, “alive” human-robot interaction. While factories and warehouses will be filled with heavy duty, rugged humanoids for labor, Companies like AheadForm is building the warm, emotionally intelligent ones for people,the kind that can smile, make eye contact, and create real connection. The future isn’t just efficient. It’s getting warmer.

🚨 This viral bionic humanoid robot company just raised hundreds of millions RMB in funding ,and it may have finally crossed the Uncanny Valley AheadForm, the startup behind those ultra-realistic face robots that have racked up hundreds of millions of views across social media, just closed a massive A1 round. This new funding will accelerate bringing these wildly popular humanoid robots into everyday life. Worth noting: Founder Yuhang Hu's latest paper on realistic lip motions for humanoid face robots has landed on the cover of Science Robotics (Jan 2026 issue). Using self-supervised AI, their robots now generate incredibly natural, continuous lip sync,supporting multiple languages, different speaking speeds, emotions, and even singing. Powered by soft silicone skin and 10+ DoF actuators, gone are the stiff puppet faces. This marks a major leap toward truly empathetic, “alive” human-robot interaction. While factories and warehouses will be filled with heavy duty, rugged humanoids for labor, Companies like AheadForm is building the warm, emotionally intelligent ones for people,the kind that can smile, make eye contact, and create real connection. The future isn’t just efficient. It’s getting warmer.

CyberRobo

112,752 Aufrufe • vor 4 Monaten

China unveils humanoid robot with lifelike skin and blinking eyes built for daily life | Prabhat Ranjan Mishra, Interesting Engineering Large Language Models (LLMs) and Vision-Language Models (VLMs) help process and interpret complex data from human interactions. A Shanghai-based company has developed humanoid robots that appear as real as humans. The advanced bionic humanoid robot is integrated with self-supervised AI algorithms. Named Elf V1, the robot can perceive the world, communicate, learn, and interact intelligently with its surroundings. Developed by AheadForm Technology, the robot offers up to 30 degrees of freedom, powered by a precise control system and an advanced AI learning algorithm. Robot offers expressive facial features The robot offers expressive facial features, moving eyes, and synchronized speech. It can also convey emotions and understand human non-verbal cues, making interactions more natural and engaging. The robot has highly interactive capabilities and lifelike appearances. AheadForm expects that its robots could soon seamlessly integrate into daily life, providing assistance, companionship, and support across various industries. “We believe that by developing realistic and expressive robot heads, we can bridge the gap between humans and machines, fostering a new era of interactive and intelligent robotics,” said the company in a statement. Reports revealed that to avoid the “uncanny valley” effect and be able to interact with us, they are given lifelike skin and capabilities to read our emotions and respond appropriately using dynamic expression simulation and emotion generation tech. Bionic skin and high-precision control system The Elf V1 series of humanoids features 30 facial muscles animated by brushless micro-motors and managed by a high-precision control system. Paired with an ability to detect their users’ emotions with low latency and bionic skin, their facial expressions are nearly identical to those of humans, reported CGTN. The company claims it’s pioneering the development of realistic humanoid robots designed to revolutionize human-robot interaction. It’s enhancing sophisticated humanoid robot heads that can express emotions, perceive their environment, and interact seamlessly with humans. By combining cutting-edge AI and advanced robotics, AheadForm aims to bring life to machines and transform how humans engage with technology. AI models boost robots’ responsiveness Seamless integration of Large Language Models (LLMs) and Vision-Language Models (VLMs) into the humanoid robots can help them process and interpret complex data from human interactions, enabling the robot to learn and adapt in real-time, achieving human-level understanding and responsiveness. AheadForm uses Brushless Motors that deliver ultra-quiet operation and high responsiveness, specifically designed for precision facial movements in humanoid robots. With its compact size, lightweight design, and energy efficiency, this motor is the ideal choice for next-generation robots that require precise, subtle facial control to create a truly human-like experience. Previously, the company unveiled the Lan Series that features realistic humanoid robots with soft skin and 10 degrees of freedom, offering a lifelike appearance and intuitive movements. This series is designed for cost-efficiency, for applications prioritizing mobility and manipulation.

China unveils humanoid robot with lifelike skin and blinking eyes built for daily life | Prabhat Ranjan Mishra, Interesting Engineering Large Language Models (LLMs) and Vision-Language Models (VLMs) help process and interpret complex data from human interactions. A Shanghai-based company has developed humanoid robots that appear as real as humans. The advanced bionic humanoid robot is integrated with self-supervised AI algorithms. Named Elf V1, the robot can perceive the world, communicate, learn, and interact intelligently with its surroundings. Developed by AheadForm Technology, the robot offers up to 30 degrees of freedom, powered by a precise control system and an advanced AI learning algorithm. Robot offers expressive facial features The robot offers expressive facial features, moving eyes, and synchronized speech. It can also convey emotions and understand human non-verbal cues, making interactions more natural and engaging. The robot has highly interactive capabilities and lifelike appearances. AheadForm expects that its robots could soon seamlessly integrate into daily life, providing assistance, companionship, and support across various industries. “We believe that by developing realistic and expressive robot heads, we can bridge the gap between humans and machines, fostering a new era of interactive and intelligent robotics,” said the company in a statement. Reports revealed that to avoid the “uncanny valley” effect and be able to interact with us, they are given lifelike skin and capabilities to read our emotions and respond appropriately using dynamic expression simulation and emotion generation tech. Bionic skin and high-precision control system The Elf V1 series of humanoids features 30 facial muscles animated by brushless micro-motors and managed by a high-precision control system. Paired with an ability to detect their users’ emotions with low latency and bionic skin, their facial expressions are nearly identical to those of humans, reported CGTN. The company claims it’s pioneering the development of realistic humanoid robots designed to revolutionize human-robot interaction. It’s enhancing sophisticated humanoid robot heads that can express emotions, perceive their environment, and interact seamlessly with humans. By combining cutting-edge AI and advanced robotics, AheadForm aims to bring life to machines and transform how humans engage with technology. AI models boost robots’ responsiveness Seamless integration of Large Language Models (LLMs) and Vision-Language Models (VLMs) into the humanoid robots can help them process and interpret complex data from human interactions, enabling the robot to learn and adapt in real-time, achieving human-level understanding and responsiveness. AheadForm uses Brushless Motors that deliver ultra-quiet operation and high responsiveness, specifically designed for precision facial movements in humanoid robots. With its compact size, lightweight design, and energy efficiency, this motor is the ideal choice for next-generation robots that require precise, subtle facial control to create a truly human-like experience. Previously, the company unveiled the Lan Series that features realistic humanoid robots with soft skin and 10 degrees of freedom, offering a lifelike appearance and intuitive movements. This series is designed for cost-efficiency, for applications prioritizing mobility and manipulation.

Owen Gregorian

179,005 Aufrufe • vor 10 Monaten

Sports like tennis are great examples of the sort of dynamic whole-body interaction that’s possible with humanoid robots. But capturing examples of fast, dynamic interactions from humans is really difficult. Enter LATENT, which uses lower-quality human data plus reinforcement learning to teach a robot to play tennis, able to complete back-and-forth volleys at a human level. LATENT has three steps: (1) collecting imperfect human data like a backswing, (2) using these to learn a latent action space, and (3) they train a high-level policy in simulation which can compose these actions and execute tennis skills on a robot. Haofei Lu and Yunrui Lian join us to tell us about their method. Watch Episode #80 of RoboPapers, with Chris Paxton and Jiafei Duan, now to learn more!

Sports like tennis are great examples of the sort of dynamic whole-body interaction that’s possible with humanoid robots. But capturing examples of fast, dynamic interactions from humans is really difficult. Enter LATENT, which uses lower-quality human data plus reinforcement learning to teach a robot to play tennis, able to complete back-and-forth volleys at a human level. LATENT has three steps: (1) collecting imperfect human data like a backswing, (2) using these to learn a latent action space, and (3) they train a high-level policy in simulation which can compose these actions and execute tennis skills on a robot. Haofei Lu and Yunrui Lian join us to tell us about their method. Watch Episode #80 of RoboPapers, with Chris Paxton and Jiafei Duan, now to learn more!

RoboPapers

30,004 Aufrufe • vor 3 Monaten

Could humanoid robots replace people on the battlefield? Compared with risking human lives — and with all the political backlash and risks of stress-induced war crimes and trauma — humanoid soldiers offer a more resilient, restrained, and precise alternative. Robots do not suffer from fatigue or fear and can operate continuously in extreme conditions while immune from radiation, chemicals, or biological agents. But the counterargument is chilling: humanoid soldiers have lower political and ethical barriers to initiating conflict, blur responsibility for any abuses, and further dehumanize warfare. In the latest episode of AI, Explained by Humans, TIME editor-at-large Charlie Campbell visited a company making these robots to see the war technology they're selling to governments around the world and interviewed experts on the potential implications. Read the full story here:

Could humanoid robots replace people on the battlefield? Compared with risking human lives — and with all the political backlash and risks of stress-induced war crimes and trauma — humanoid soldiers offer a more resilient, restrained, and precise alternative. Robots do not suffer from fatigue or fear and can operate continuously in extreme conditions while immune from radiation, chemicals, or biological agents. But the counterargument is chilling: humanoid soldiers have lower political and ethical barriers to initiating conflict, blur responsibility for any abuses, and further dehumanize warfare. In the latest episode of AI, Explained by Humans, TIME editor-at-large Charlie Campbell visited a company making these robots to see the war technology they're selling to governments around the world and interviewed experts on the potential implications. Read the full story here:

TIME

12,152 Aufrufe • vor 4 Monaten

Humanoid robot convenience stores are becoming a part of people's lives. A couple of days ago, I passed by the Zhangjiang AI Town in Shanghai. At the GalBOT "Space Capsule," I bought a bottle of Coca-Cola from a convenience store operated by a humanoid robot. It was smoother than I expected: screen selection, QR code payment, and the humanoid robot G1 retrieving and delivering the goods – all in one seamless process. It's worth noting that a human worker was still present inside, handling emergency situations. However, it can't yet take orders through speech, but this will change soon. People will be able to shop by naturally conversing with G1, paying with palm or facial recognition (e.g., Alipay), and the humanoid robot will autonomously fulfill orders without ever getting tired, always full of enthusiasm and patience. It is expected that convenience stores operated by humanoid robots will soon appear in the core areas and tourist zones of many Chinese cities this year, with companies like GalBOT, Astribot, and AI² Robotics deploying them in large numbers. Its value goes beyond simply achieving intelligent automation in retail; it's becoming an integral part of people's future technological lives.

Humanoid robot convenience stores are becoming a part of people's lives. A couple of days ago, I passed by the Zhangjiang AI Town in Shanghai. At the GalBOT "Space Capsule," I bought a bottle of Coca-Cola from a convenience store operated by a humanoid robot. It was smoother than I expected: screen selection, QR code payment, and the humanoid robot G1 retrieving and delivering the goods – all in one seamless process. It's worth noting that a human worker was still present inside, handling emergency situations. However, it can't yet take orders through speech, but this will change soon. People will be able to shop by naturally conversing with G1, paying with palm or facial recognition (e.g., Alipay), and the humanoid robot will autonomously fulfill orders without ever getting tired, always full of enthusiasm and patience. It is expected that convenience stores operated by humanoid robots will soon appear in the core areas and tourist zones of many Chinese cities this year, with companies like GalBOT, Astribot, and AI² Robotics deploying them in large numbers. Its value goes beyond simply achieving intelligent automation in retail; it's becoming an integral part of people's future technological lives.

CyberRobo

42,073 Aufrufe • vor 7 Monaten

Elon Musk envisions a future where everyone gets access to the world's best surgeons—because Tesla's Optimus robots will deliver superhuman precision for any medical procedure, even ones too complex for humans. "Imagine a world where everyone has access to the best surgeons, literally everyone... Optimus will have the level of precision that is frankly superhuman... and that will be available to anyone." Money can't scale top doctors—they're rare. But robots? Built in factories at scale. From scarcity to abundance: Could humanoid robots truly end healthcare inequality? Would you trust an Optimus robot for surgery if it outperformed humans? Or is the human touch irreplaceable? What's your take on this bold vision? Drop thoughts below.

Elon Musk envisions a future where everyone gets access to the world's best surgeons—because Tesla's Optimus robots will deliver superhuman precision for any medical procedure, even ones too complex for humans. "Imagine a world where everyone has access to the best surgeons, literally everyone... Optimus will have the level of precision that is frankly superhuman... and that will be available to anyone." Money can't scale top doctors—they're rare. But robots? Built in factories at scale. From scarcity to abundance: Could humanoid robots truly end healthcare inequality? Would you trust an Optimus robot for surgery if it outperformed humans? Or is the human touch irreplaceable? What's your take on this bold vision? Drop thoughts below.

Camus

11,255 Aufrufe • vor 6 Monaten

NEO robot achieves “almost human-like” hand dexterity The Norwegian-American startup 1X has demonstrated new capabilities of its humanoid robot NEO — it has learned to perform fine motor tasks at a level close to humans. The robot can assemble Lego, eat chips, play video games, screw in a light bulb, pick a grape, and carefully hold a wine glass. Previously, one of the biggest challenges for robots was handling small objects — they struggled to understand how much force was needed to grip them. NEO solves this problem with cable-driven actuators and a force-control system: each joint moves the finger while simultaneously measuring pressure. The developers believe these technologies could become an important step toward the creation of universal home robots.

NEO robot achieves “almost human-like” hand dexterity The Norwegian-American startup 1X has demonstrated new capabilities of its humanoid robot NEO — it has learned to perform fine motor tasks at a level close to humans. The robot can assemble Lego, eat chips, play video games, screw in a light bulb, pick a grape, and carefully hold a wine glass. Previously, one of the biggest challenges for robots was handling small objects — they struggled to understand how much force was needed to grip them. NEO solves this problem with cable-driven actuators and a force-control system: each joint moves the finger while simultaneously measuring pressure. The developers believe these technologies could become an important step toward the creation of universal home robots.

NEXTA

45,406 Aufrufe • vor 1 Monat

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

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

CyberRobo

46,782 Aufrufe • vor 3 Monaten

Ashok Elluswamy, Tesla's AI lead, during a GTC discussion, highlighting the fundamental similarity in AI approaches for self-driving cars and humanoid robots: - Hierarchical decision making is useful, but it has to be done as part of the same decision-making process as lower-level controls. - We haven't seen the long tail of humanoid robotics, but Tesla has seen the long tail of self-driving, where high and low-level decisions have to be jointly made at a pretty high framerate. - Optimus's architecture is designed in a similar way, where there's a hierarchy but it's all running as part of the same model and the latencies involved in decision making are well modeled. - This architecture will scale quite well with humanoid robots. - The distinction of the decision-making levels is only in the developer's mind. For the model, it's a continuous space of decision making, where there are dials available to make them more fine or coarse. - Humanoids have more sensor modalities and higher degrees of freedom compared to self-driving, but the fundamental constraints remain the same: you need to make real-time decisions. There's obviously a hierarchy to these control signal outputs, but the lowest frequency cannot be too low, because the safety of the robot cannot depend upon things running at very low frequencies.

Ashok Elluswamy, Tesla's AI lead, during a GTC discussion, highlighting the fundamental similarity in AI approaches for self-driving cars and humanoid robots: - Hierarchical decision making is useful, but it has to be done as part of the same decision-making process as lower-level controls. - We haven't seen the long tail of humanoid robotics, but Tesla has seen the long tail of self-driving, where high and low-level decisions have to be jointly made at a pretty high framerate. - Optimus's architecture is designed in a similar way, where there's a hierarchy but it's all running as part of the same model and the latencies involved in decision making are well modeled. - This architecture will scale quite well with humanoid robots. - The distinction of the decision-making levels is only in the developer's mind. For the model, it's a continuous space of decision making, where there are dials available to make them more fine or coarse. - Humanoids have more sensor modalities and higher degrees of freedom compared to self-driving, but the fundamental constraints remain the same: you need to make real-time decisions. There's obviously a hierarchy to these control signal outputs, but the lowest frequency cannot be too low, because the safety of the robot cannot depend upon things running at very low frequencies.

The Humanoid Hub

669,921 Aufrufe • vor 5 Monaten

Imagine knowing the building you are entering could collapse within next few seconds or minutes! Yet without a second thought for his own safety he rushed in to evacuate everyone inside before tragedy could strike! That is courage! And this was his first day as SHO Beerwah! We often criticize the police but moments like these remind us that they are human too! They have families waiting for them at home, yet they willingly risk their lives to protect ours! A big round of applause and heartfelt respect to this brave man and the policemen who stood by him! 👏🫡

Imagine knowing the building you are entering could collapse within next few seconds or minutes! Yet without a second thought for his own safety he rushed in to evacuate everyone inside before tragedy could strike! That is courage! And this was his first day as SHO Beerwah! We often criticize the police but moments like these remind us that they are human too! They have families waiting for them at home, yet they willingly risk their lives to protect ours! A big round of applause and heartfelt respect to this brave man and the policemen who stood by him! 👏🫡

Tahir Peerzada

36,628 Aufrufe • vor 27 Tagen

Sub-1 hour? Chasing the human half-marathon record? That’s suddenly the conversation around Beijing’s humanoid robot race this Sunday. 🏃‍♂️🤖 A year ago, this event was mostly about finishing. Now the bar is speed, stability, and full-course autonomy. More than 100 teams and 300+ humanoid robots are expected on the line, and nearly 40% of them are entering the autonomous navigation group instead of relying on remote control. The course is not getting easier either. Same 21.0975 km, but with more urban slopes, rolling sections, and park terrain built to expose weak points in control, perception, and endurance. That is what makes this race worth watching. If some of these machines really get close to one hour, the story is no longer “robots can run.” It becomes “humanoids are starting to hold speed, balance, and navigation together over real distance.” And that matters far beyond a race course. This is one of the clearest public tests yet for where humanoid robotics actually stands in hardware, motion control, power systems, and autonomous mobility. Sunday’s headline will be the time. The bigger takeaway will be how much of that pace is still there at kilometer 15, 18, and 21. I want to see who is actually fast, who is truly autonomous, and who can finish without falling apart. That is where the real signal will be.

Sub-1 hour? Chasing the human half-marathon record? That’s suddenly the conversation around Beijing’s humanoid robot race this Sunday. 🏃‍♂️🤖 A year ago, this event was mostly about finishing. Now the bar is speed, stability, and full-course autonomy. More than 100 teams and 300+ humanoid robots are expected on the line, and nearly 40% of them are entering the autonomous navigation group instead of relying on remote control. The course is not getting easier either. Same 21.0975 km, but with more urban slopes, rolling sections, and park terrain built to expose weak points in control, perception, and endurance. That is what makes this race worth watching. If some of these machines really get close to one hour, the story is no longer “robots can run.” It becomes “humanoids are starting to hold speed, balance, and navigation together over real distance.” And that matters far beyond a race course. This is one of the clearest public tests yet for where humanoid robotics actually stands in hardware, motion control, power systems, and autonomous mobility. Sunday’s headline will be the time. The bigger takeaway will be how much of that pace is still there at kilometer 15, 18, and 21. I want to see who is actually fast, who is truly autonomous, and who can finish without falling apart. That is where the real signal will be.

RoboHub🤖

209,946 Aufrufe • vor 4 Monaten

Ex Machina is no longer sci-fi. China has finally built it. The company is AheadForm, founded in Shanghai. The product is the world's most hyper-realistic robotic face. Silicone skin you can't tell from human, 25 micro motors hidden underneath pulling the face into real expressions. And RGB cameras embedded inside the pupils so when it looks at you, it actually sees you from where its eyes are. They raised $28.5M to "give AI a head," which is also where the name comes from. AheadForm = a head form. This is the opposite of where everyone else in robotics is focused. Unitree, Figure, Tesla, Boston Dynamics: all about the body. AheadForm chose the face because they think trust is the harder problem to solve, and trust gets decided at the face. The reason nobody else has tried this is the "uncanny valley." It's the creepy zone where a robot looks almost human but not quite, and looking at it just feels wrong even when you can't say why. Most roboticists believed no amount of engineering could make a face realistic enough to escape it. So they gave up and kept robots cartoonish on purpose: big anime eyes, exaggerated features, clearly synthetic. But AheadForm decided to treat it as an engineering bug instead. Add enough motors, tune the silicone, fix the timing, the valley closes. And they're pulling it off. A few crazy details about how this actually works: 1. The robot learns its own face in a mirror. You put it in front of a camera, let it fire every motor randomly, and it watches what its face does and builds an internal map of "if I send command X to motor Y, my eyebrow does this." Same exact process a human baby uses staring into a mirror. The robot teaches itself who it is by experimenting. 2. It predicts your smile 839 milliseconds before you smile. By watching the micro-tells in your face that precede a smile, the robot starts smiling 0.8 seconds ahead, so its smile lands at the same moment yours does. Most robot mimicry happens half a second late, which is exactly why it always feels artificial. 3. The pupils are the cameras. When the robot makes eye contact, the gaze and the sensor are the same physical thing. Most humanoid robots stick the camera on the forehead or chest, so they aren't actually looking at you when their eyes are pointed at you. 4. The founder, Yuhang Hu, did his PhD at Columbia under Hod Lipson. Lipson is the guy who in 2006 built a four-legged robot that figured out it had four legs by experimenting with its own movement, nobody told it the body shape, it discovered it. He has spent 25 years trying to build machines that know what they are. AheadForm is that 25-year research arc productized. 5. NetEase Games already paid them to physically embody a fantasy video game character. That opens up a brand-new category: robotics as the physical embodiment of fictional IP. Every character-rich studio, Disney, Riot, Hoyoverse, Pokemon, Netflix, now has a question to answer about when their characters get bodies. AheadForm believes whoever ships the first robot you'd actually want around your family wins. That's the bet behind the most realistic robot face on earth.

Ole Lehmann

536,041 Aufrufe • vor 3 Monaten

I don’t know if we live in a Matrix, but I know for sure that robots will spend most of their lives in simulation. Let machines train machines. I’m excited to introduce DexMimicGen, a massive-scale synthetic data generator that enables a humanoid robot to learn complex skills from only a handful of human demonstrations. Yes, as few as 5! DexMimicGen addresses the biggest pain point in robotics: where do we get data? Unlike with LLMs, where vast amounts of texts are readily available, you cannot simply download motor control signals from the internet. So researchers teleoperate the robots to collect motion data via XR headsets. They have to repeat the same skill over and over and over again, because neural nets are data hungry. This is a very slow and uncomfortable process. At NVIDIA, we believe the majority of high-quality tokens for robot foundation models will come from simulation. What DexMimicGen does is to trade GPU compute time for human time. It takes one motion trajectory from human, and multiplies into 1000s of new trajectories. A robot brain trained on this augmented dataset will generalize far better in the real world. Think of DexMimicGen as a learning signal amplifier. It maps a small dataset to a large (de facto infinite) dataset, using physics simulation in the loop. In this way, we free humans from babysitting the bots all day. The future of robot data is generative. The future of the entire robot learning pipeline will also be generative. 🧵

I don’t know if we live in a Matrix, but I know for sure that robots will spend most of their lives in simulation. Let machines train machines. I’m excited to introduce DexMimicGen, a massive-scale synthetic data generator that enables a humanoid robot to learn complex skills from only a handful of human demonstrations. Yes, as few as 5! DexMimicGen addresses the biggest pain point in robotics: where do we get data? Unlike with LLMs, where vast amounts of texts are readily available, you cannot simply download motor control signals from the internet. So researchers teleoperate the robots to collect motion data via XR headsets. They have to repeat the same skill over and over and over again, because neural nets are data hungry. This is a very slow and uncomfortable process. At NVIDIA, we believe the majority of high-quality tokens for robot foundation models will come from simulation. What DexMimicGen does is to trade GPU compute time for human time. It takes one motion trajectory from human, and multiplies into 1000s of new trajectories. A robot brain trained on this augmented dataset will generalize far better in the real world. Think of DexMimicGen as a learning signal amplifier. It maps a small dataset to a large (de facto infinite) dataset, using physics simulation in the loop. In this way, we free humans from babysitting the bots all day. The future of robot data is generative. The future of the entire robot learning pipeline will also be generative. 🧵

Jim Fan

165,246 Aufrufe • vor 1 Jahr

Vidaio 2026 Roadmap (and a bit of 2025): Building The Next Phase of AI-Driven Video Infrastructure We listened to the market and are building practical, sought-after, real-world applicable products. Our 2026 roadmap is focused on automation, intelligence, accessibility, and scale. It’s ambitious, but so are we! Here’s what’s live….. and what we’re building next! (If there are too many words below, just watch this awesome video created by the legendary DankEngine (τ,τ)) Core Infrastructure (Live) - Launched: April 1st Market need: Decentralised, affordable, scalable video processing for high-volume video workloads. The subnet forms the backbone for AI-driven video tasks, enabling: -Parallel processing -Cost efficiency at scale -Continuous product innovation AI Video Upscaling (Live) Market need: Re-purposing legacy content for modern screens. Upscaling unlocks: -Reuse of legacy SD/HD content -Platform-ready delivery for modern displays -Reduced re-production costs Video Compression (Live) Market need: Reduce rising storage and delivery costs while maintaining high perceptual quality. Our AI-driven compression pipeline is designed to: -Optimise bitrate without perceptual quality loss -Support modern codecs -Reduce CDN and storage costs at scale Vidaio Studio (Live) Market need: AI- Driven engineering-grade control in one UI Features: -Multiple codecs -Multiple resolutions -Flexible encoding modes Advanced Post Production tools Market need: Automation replacing manual post-production. Coming enhancements: -Frame rate conversion -Colour correction -HDR processing -De-noise -Stabilisation These capabilities shift traditionally manual workflows into real-time AI processing. GenAI Video Enhancement Market need: Unparalleled video quality enhancement GenAI models enable: -Content-aware enhancement -Scene-level optimisation -Reviving bad quality and unusable content Access Services (New Pillar) Market need: Regulation, inclusivity, and global reach. Built-in accessibility services: -Subtitles -Closed captions -Audio description Accessibility is no longer optional; it’s required legislation. Video Streaming Market need: Low latency, high quality, decentralised streaming. Our streaming roadmap focuses on: -Optimised delivery pipelines -Leveraging current video processing tools -Decentralised delivery Truly decentralised, high-quality video streaming run on the Bittensor network. AI Colourisation Market need: Reviving legacy content and accelerating localisation. AI colourisation enables: -Restoration of black-and-white and faded archival footage -Faster remastering pipelines for broadcasters and studios -Consistent colour application at scale without manual grading Unlocking new commercial value from existing libraries. GenAI Lip Sync Market need: Localisation, dubbing, and global content expansion. GenAI lip sync enables: -High-quality localisation -Bringing premium content to multiple new audiences -Natural facial motion via advanced face-mapping workflows Meet the growing demand for multilingual content by delivering seamless lip syncing.

Vidaio 2026 Roadmap (and a bit of 2025): Building The Next Phase of AI-Driven Video Infrastructure We listened to the market and are building practical, sought-after, real-world applicable products. Our 2026 roadmap is focused on automation, intelligence, accessibility, and scale. It’s ambitious, but so are we! Here’s what’s live….. and what we’re building next! (If there are too many words below, just watch this awesome video created by the legendary DankEngine (τ,τ)) Core Infrastructure (Live) - Launched: April 1st Market need: Decentralised, affordable, scalable video processing for high-volume video workloads. The subnet forms the backbone for AI-driven video tasks, enabling: -Parallel processing -Cost efficiency at scale -Continuous product innovation AI Video Upscaling (Live) Market need: Re-purposing legacy content for modern screens. Upscaling unlocks: -Reuse of legacy SD/HD content -Platform-ready delivery for modern displays -Reduced re-production costs Video Compression (Live) Market need: Reduce rising storage and delivery costs while maintaining high perceptual quality. Our AI-driven compression pipeline is designed to: -Optimise bitrate without perceptual quality loss -Support modern codecs -Reduce CDN and storage costs at scale Vidaio Studio (Live) Market need: AI- Driven engineering-grade control in one UI Features: -Multiple codecs -Multiple resolutions -Flexible encoding modes Advanced Post Production tools Market need: Automation replacing manual post-production. Coming enhancements: -Frame rate conversion -Colour correction -HDR processing -De-noise -Stabilisation These capabilities shift traditionally manual workflows into real-time AI processing. GenAI Video Enhancement Market need: Unparalleled video quality enhancement GenAI models enable: -Content-aware enhancement -Scene-level optimisation -Reviving bad quality and unusable content Access Services (New Pillar) Market need: Regulation, inclusivity, and global reach. Built-in accessibility services: -Subtitles -Closed captions -Audio description Accessibility is no longer optional; it’s required legislation. Video Streaming Market need: Low latency, high quality, decentralised streaming. Our streaming roadmap focuses on: -Optimised delivery pipelines -Leveraging current video processing tools -Decentralised delivery Truly decentralised, high-quality video streaming run on the Bittensor network. AI Colourisation Market need: Reviving legacy content and accelerating localisation. AI colourisation enables: -Restoration of black-and-white and faded archival footage -Faster remastering pipelines for broadcasters and studios -Consistent colour application at scale without manual grading Unlocking new commercial value from existing libraries. GenAI Lip Sync Market need: Localisation, dubbing, and global content expansion. GenAI lip sync enables: -High-quality localisation -Bringing premium content to multiple new audiences -Natural facial motion via advanced face-mapping workflows Meet the growing demand for multilingual content by delivering seamless lip syncing.

Vidaio

16,996 Aufrufe • vor 7 Monaten