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Apple's AI researchers introduce EMOTION, a framework for expressive humanoid gestures. ⦿ LLMs interpret social context and generate motions from human demos ⦿ Robots execute motions via inverse kinematics ⦿ Gestures are refined through human feedback Hardware: Fourier GR-1

The Humanoid Hub

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66,831 Aufrufe • vor 1 Jahr •via X (Twitter)

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Profilbild von The Humanoid Hub

The Humanoid Hubvor 1 Jahr

Paper:

Profilbild von AssemblyAI

AssemblyAIvor 1 Jahr

Announcing: Our most advanced speech-to-text model goes beyond accuracy to capture the real-world complexity of human conversation and deliver reliable, source-of-truth audio data. Explore Universal-2 updates 👇

Profilbild von Tom Löwe

Tom Löwevor 1 Jahr

If Apple was smart, they would be pouring all of their available resources into building a humanoid robot.

Profilbild von Ai Handbook 🔖

Ai Handbook 🔖vor 1 Jahr

Mate, this robotic field with AI is getting crazy! I really wonder when we use these in our homes on a daily basis.

Profilbild von Gahro

Gahrovor 1 Jahr

I read "Human Retarded"

Profilbild von Marcus van der Erve✨

Marcus van der Erve✨vor 1 Jahr

Simplistic

Profilbild von ADEBIG💎 (✸,✸) (✸,✸) ⛺

ADEBIG💎 (✸,✸) (✸,✸) ⛺vor 1 Jahr

Looks like robots are getting in touch with their feelings! With PublicAI, we can teach them to express gratitude for all the data we provide! 😂🤖

Profilbild von Ngoc Nguyễn

Ngoc Nguyễnvor 1 Jahr

Looks like robots are getting their groove on! 🤖💃 With PublicAI, we can add some top-notch training data to help them nail those gestures! #AI #DanceOff

Profilbild von Elvis Efe

Elvis Efevor 1 Jahr

Looks like Apple’s robots are getting a crash course in human emotions! At PublicAI, we’re all about bridging gaps too—just with a bit more data and a lot more fun! 🤖✨

Profilbild von SÅÏDĖÑ

SÅÏDĖÑvor 1 Jahr

Wow 😵‍💫

Profilbild von Appy Pie

Appy Pievor 1 Jahr

Apple is stepping up its AI game! Expressive humanoid gestures could revolutionize human-robot interaction.

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2. NVIDIA is building the GPT of humanoid robots. They just launched Isaac GR00T N1.5 - a foundation model for general purpose robotics. Here’s how it works: → A human demos the task once → Cosmos (their physics AI model) generates 1,000s of variations → Omniverse simulates the motions in high fidelity → The robot trains entirely in simulation → Then fine-tunes itself in the real world Robots can now learn general skills across tasks, tools, even body types with just one human demo. AI isn’t just thinking in text anymore. It’s perceiving. Reasoning. Moving. Physical AI is here and it’s training itself.

2. NVIDIA is building the GPT of humanoid robots. They just launched Isaac GR00T N1.5 - a foundation model for general purpose robotics. Here’s how it works: → A human demos the task once → Cosmos (their physics AI model) generates 1,000s of variations → Omniverse simulates the motions in high fidelity → The robot trains entirely in simulation → Then fine-tunes itself in the real world Robots can now learn general skills across tasks, tools, even body types with just one human demo. AI isn’t just thinking in text anymore. It’s perceiving. Reasoning. Moving. Physical AI is here and it’s training itself.

Shruti

70,359 Aufrufe • vor 1 Jahr

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 9 Monaten

Humanoid robots are cool. But most of them aren’t ready for real-world work. X-Humanoid just launched Embodied Tien Kung 3.0 - a full-size humanoid robot built to actually operate in industrial and commercial environments. What makes it different? • Strong, high-torque joints for heavy tasks • Can move dynamically and stay stable • Handles complex motions (even over obstacles) • Millimeter-level precision for detailed work It runs on the Wise KaiWu AI platform, which allows the robot to see, think, and act in a continuous loop with less human control and support for multi-robot collaboration. It also supports ROS2, MQTT, and TCP/IP, and offers more open hardware + software interfaces to make development easier for teams. The goal is simple: make humanoid robots practical, easier to build on, and ready for real-world use. Visit: Check out the official launch video below to see what it can do! 👇 #Robotics #HumanoidRobot #AI

Humanoid robots are cool. But most of them aren’t ready for real-world work. X-Humanoid just launched Embodied Tien Kung 3.0 - a full-size humanoid robot built to actually operate in industrial and commercial environments. What makes it different? • Strong, high-torque joints for heavy tasks • Can move dynamically and stay stable • Handles complex motions (even over obstacles) • Millimeter-level precision for detailed work It runs on the Wise KaiWu AI platform, which allows the robot to see, think, and act in a continuous loop with less human control and support for multi-robot collaboration. It also supports ROS2, MQTT, and TCP/IP, and offers more open hardware + software interfaces to make development easier for teams. The goal is simple: make humanoid robots practical, easier to build on, and ready for real-world use. Visit: Check out the official launch video below to see what it can do! 👇 #Robotics #HumanoidRobot #AI

Chidanand Tripathi

69,604 Aufrufe • vor 4 Monaten

Humanoids finally move like humans… and can do more than copy. [Details + demos in thread 👇] A new framework, BeyondMimic, shows how to learn naturalistic whole-body control from human motion. But then goes further by composing those skills into versatile, zero-shot policies. Two key pieces make it work: •Motion tracking pipeline: robustly turns human mocap into dynamic robot motions (jump spins, sprinting, cartwheels) on real hardware •Guided diffusion policy: distills motion primitives and enables zero-shot downstream tasks with simple cost functions The result: ✅ State-of-the-art motion quality from mocap tracking ✅ Versatile task execution; waypoint navigation, joystick teleop, obstacle avoidance ✅ Stable sim-to-real transfer for diverse humanoid skills Thank you for sharing, Qiayuan Liao! 📍 Paper: Video:

Humanoids finally move like humans… and can do more than copy. [Details + demos in thread 👇] A new framework, BeyondMimic, shows how to learn naturalistic whole-body control from human motion. But then goes further by composing those skills into versatile, zero-shot policies. Two key pieces make it work: •Motion tracking pipeline: robustly turns human mocap into dynamic robot motions (jump spins, sprinting, cartwheels) on real hardware •Guided diffusion policy: distills motion primitives and enables zero-shot downstream tasks with simple cost functions The result: ✅ State-of-the-art motion quality from mocap tracking ✅ Versatile task execution; waypoint navigation, joystick teleop, obstacle avoidance ✅ Stable sim-to-real transfer for diverse humanoid skills Thank you for sharing, Qiayuan Liao! 📍 Paper: Video:

Ilir Aliu - eu/acc

72,522 Aufrufe • vor 11 Monaten

The power of generative models — now embodied in humanoids. Announcing DreamControl –– After a year-long research effort at General Robotics — we present a scalable framework for whole-body humanoid control that fuses diffusion priors with reinforcement learning to unlock real-world scene interaction. Diffusion + RL → natural whole-body skills on real robots. DreamControl enables humanoids to move beyond locomotion demos → performing natural, human-like skills such as –– Picking & lifting objects, Opening drawers & doors, Precise punching, kicking, and jumping, Bimanual manipulation tasks Our key innovation: a diffusion prior over human motion that guides RL, eliminating the need for massive teleoperation datasets, and producing motions that look human while transferring to real hardware. Trained purely in simulation, deployed on the Unitree G1 humanoid, DreamControl policies run in real time, bridging sim-to-real with unprecedented naturalness. We leverage a novel hybrid edge + cloud infrastructure that runs RL-trained policies on the edge backed by powerful AI models running in the cloud This is the next step in General Robotics’ journey toward general-purpose humanoid assistants that interact, adapt, and assist autonomously. Paper: Blog: 1/n

The power of generative models — now embodied in humanoids. Announcing DreamControl –– After a year-long research effort at General Robotics — we present a scalable framework for whole-body humanoid control that fuses diffusion priors with reinforcement learning to unlock real-world scene interaction. Diffusion + RL → natural whole-body skills on real robots. DreamControl enables humanoids to move beyond locomotion demos → performing natural, human-like skills such as –– Picking & lifting objects, Opening drawers & doors, Precise punching, kicking, and jumping, Bimanual manipulation tasks Our key innovation: a diffusion prior over human motion that guides RL, eliminating the need for massive teleoperation datasets, and producing motions that look human while transferring to real hardware. Trained purely in simulation, deployed on the Unitree G1 humanoid, DreamControl policies run in real time, bridging sim-to-real with unprecedented naturalness. We leverage a novel hybrid edge + cloud infrastructure that runs RL-trained policies on the edge backed by powerful AI models running in the cloud This is the next step in General Robotics’ journey toward general-purpose humanoid assistants that interact, adapt, and assist autonomously. Paper: Blog: 1/n

Ashish Kapoor

118,133 Aufrufe • vor 10 Monaten

This perspective will be more intuitive. Fourier is building a data acquisition and training platform that integrates non-invasive brain-computer interfaces and humanoid robots. This wealth of data will enhance the intelligence level of GR-3. The goal is for GR-3 to accurately identify the brain intention signals of stroke patients during future rehabilitation training and respond in real time to guide patients in performing rehabilitation movements. For example, lifting the left hand, picking up a block from the table, etc. Of course, GR-3 can also become a life assistant controlled by a human BCI. Imagine that people with mobility impairments could also issue commands to GR-3 via BCI to open the refrigerator and get a drink.

This perspective will be more intuitive. Fourier is building a data acquisition and training platform that integrates non-invasive brain-computer interfaces and humanoid robots. This wealth of data will enhance the intelligence level of GR-3. The goal is for GR-3 to accurately identify the brain intention signals of stroke patients during future rehabilitation training and respond in real time to guide patients in performing rehabilitation movements. For example, lifting the left hand, picking up a block from the table, etc. Of course, GR-3 can also become a life assistant controlled by a human BCI. Imagine that people with mobility impairments could also issue commands to GR-3 via BCI to open the refrigerator and get a drink.

CyberRobo

18,624 Aufrufe • vor 5 Monaten

Excited to share our latest work on 🎧spatial audio-driven human motion generation. We aim to tackle a largely underexplored yet important problem of enabling virtual humans to move naturally in response to spatial audio—capturing not just what is heard, but also where the sound is coming from. To this end, we introduce the Spatial Audio-Driven Human Motion (SAM) dataset—the first comprehensive dataset featuring paired high-quality human motion and spatial audio recordings. For benchmarking, we develop a generative framework for human MOtion generation driven by SPAtial audio, termed MOSPA, which learns to synthesize realistic and diverse human motions conditioned on spatial audio input. We hope this research could provide a foundation for future research in spatial perception, virtual characters, and embodied AI. The dataset and model will be open-sourced soon. A big thank you to our intern, Shuyang Xu, for the wonderful collaboration! Congratulations, Shuyang! Project page: Paper: Video: #Animation #CG #CV #AIGC #DL #Deeplearning #Motion #Graphics #AI #GenerativeAI

Excited to share our latest work on 🎧spatial audio-driven human motion generation. We aim to tackle a largely underexplored yet important problem of enabling virtual humans to move naturally in response to spatial audio—capturing not just what is heard, but also where the sound is coming from. To this end, we introduce the Spatial Audio-Driven Human Motion (SAM) dataset—the first comprehensive dataset featuring paired high-quality human motion and spatial audio recordings. For benchmarking, we develop a generative framework for human MOtion generation driven by SPAtial audio, termed MOSPA, which learns to synthesize realistic and diverse human motions conditioned on spatial audio input. We hope this research could provide a foundation for future research in spatial perception, virtual characters, and embodied AI. The dataset and model will be open-sourced soon. A big thank you to our intern, Shuyang Xu, for the wonderful collaboration! Congratulations, Shuyang! Project page: Paper: Video: #Animation #CG #CV #AIGC #DL #Deeplearning #Motion #Graphics #AI #GenerativeAI

Zhiyang (Frank) Dou

14,610 Aufrufe • vor 1 Jahr

Video: China firm to unveil world’s most ‘adorable’ humanoid robot for homes, schools | Christopher McFadden, Interesting Engineering Fourier’s latest humanoid robot, the GR‑3, is designed for domestic and educational environments. Fourier Robotics, the Shanghai-based robotics firm behind the GR-1 and GR-2 models, is preparing to launch its GR-3 humanoid robot on August 6. Early glimpses of the new robot, including a sneak-peek video, reveal a smaller, friendlier design, described as possibly the “most adorable humanoid robot yet.” Concrete information is scarce, but early reports suggest the robot will be smaller than its predecessors. According to some reports, the GR-3 will likely stand at around 4 feet 5 inches (134 cm). This makes it notably smaller than the earlier GR-1 (5.4 feet/165 cm) and GR-2 (5.74 feet/175 cm) models from Fourier. Most notable is its apparent “softer,” almost cuddly aesthetic.” The robot is likely intended for use in homes, schools, hospitals, and public spaces. It also features an integrated large language model (LLM) to enable natural speech engagement with users. To this end, the GR-3 will likely be marked as a companion‑style or caregiver bot (AKA a “Care‑bot”) aimed at friendly human interaction in personal or learning environments. GR-3: Fourier’s cutest robot yet “This softer aesthetic is a nice change compared to the usual designs we see with humanoid robots. The eyes are a much-needed touch,” comments a member on the Companian Robot Forums. “It’s so expressive and draws you in. Can’t wait to see what this looks like. Hopefully it is reasonably priced. Could definitely see myself owning one of these,” they added. The GR-3 is a natural progression of the company’s previous models. The first, the GR-1, was launched by Foureir in 2023 and was its first mass-targeted humanoid, featuring 44 joints and capable of walking at 3.1 mph (5 kph). Capable of carrying around 6.6. pounds (3 kg) of weight, it featured advanced perception via six RGB cameras that formed real-time 3D occupancy grids, an LLM-based emotional interaction system, and modular Fourier Smart Actuators (FSA) delivering around 230 N/m of torque. The GR-2 was debuted in 2024 and raised the bar with a taller frame (~175 cm, 63 kg), 53 degrees of freedom, enhanced 12 degrees of freedom (DoF) dexterous hands with tactile sensors, and power-dense FSA 2.0 actuators (around 380 N/m torque). Given this lineage, the GR-3 is likely to continue innovating in areas such as compact hardware design, featuring a shorter, lighter frame tailored to domestic spaces. It will also build on the company’s focus on friendly user interaction thanks to its softer aesthetic and approachable interface. The GR-3 will also likely feature use-case-specific actuation and sensing, likely simpler than the GR-2’s high-precision hands but optimized for social or light domestic tasks. Scheduled for release in August It will likely also feature an accessible software stack continuing Fourier’s support for developers via pre‑built APIs and possibly integration with LLMs and vision systems. Fourier has confirmed the robot’s official reveal is scheduled for early August, with teaser posts on X and robotics forums generating anticipation among fans and researchers. When formally revealed, the GR‑3 could represent Fourier’s first small-form social humanoid, bridging the gap between research platforms and home or classroom robots. Read more:

Video: China firm to unveil world’s most ‘adorable’ humanoid robot for homes, schools | Christopher McFadden, Interesting Engineering Fourier’s latest humanoid robot, the GR‑3, is designed for domestic and educational environments. Fourier Robotics, the Shanghai-based robotics firm behind the GR-1 and GR-2 models, is preparing to launch its GR-3 humanoid robot on August 6. Early glimpses of the new robot, including a sneak-peek video, reveal a smaller, friendlier design, described as possibly the “most adorable humanoid robot yet.” Concrete information is scarce, but early reports suggest the robot will be smaller than its predecessors. According to some reports, the GR-3 will likely stand at around 4 feet 5 inches (134 cm). This makes it notably smaller than the earlier GR-1 (5.4 feet/165 cm) and GR-2 (5.74 feet/175 cm) models from Fourier. Most notable is its apparent “softer,” almost cuddly aesthetic.” The robot is likely intended for use in homes, schools, hospitals, and public spaces. It also features an integrated large language model (LLM) to enable natural speech engagement with users. To this end, the GR-3 will likely be marked as a companion‑style or caregiver bot (AKA a “Care‑bot”) aimed at friendly human interaction in personal or learning environments. GR-3: Fourier’s cutest robot yet “This softer aesthetic is a nice change compared to the usual designs we see with humanoid robots. The eyes are a much-needed touch,” comments a member on the Companian Robot Forums. “It’s so expressive and draws you in. Can’t wait to see what this looks like. Hopefully it is reasonably priced. Could definitely see myself owning one of these,” they added. The GR-3 is a natural progression of the company’s previous models. The first, the GR-1, was launched by Foureir in 2023 and was its first mass-targeted humanoid, featuring 44 joints and capable of walking at 3.1 mph (5 kph). Capable of carrying around 6.6. pounds (3 kg) of weight, it featured advanced perception via six RGB cameras that formed real-time 3D occupancy grids, an LLM-based emotional interaction system, and modular Fourier Smart Actuators (FSA) delivering around 230 N/m of torque. The GR-2 was debuted in 2024 and raised the bar with a taller frame (~175 cm, 63 kg), 53 degrees of freedom, enhanced 12 degrees of freedom (DoF) dexterous hands with tactile sensors, and power-dense FSA 2.0 actuators (around 380 N/m torque). Given this lineage, the GR-3 is likely to continue innovating in areas such as compact hardware design, featuring a shorter, lighter frame tailored to domestic spaces. It will also build on the company’s focus on friendly user interaction thanks to its softer aesthetic and approachable interface. The GR-3 will also likely feature use-case-specific actuation and sensing, likely simpler than the GR-2’s high-precision hands but optimized for social or light domestic tasks. Scheduled for release in August It will likely also feature an accessible software stack continuing Fourier’s support for developers via pre‑built APIs and possibly integration with LLMs and vision systems. Fourier has confirmed the robot’s official reveal is scheduled for early August, with teaser posts on X and robotics forums generating anticipation among fans and researchers. When formally revealed, the GR‑3 could represent Fourier’s first small-form social humanoid, bridging the gap between research platforms and home or classroom robots. Read more:

Owen Gregorian

64,074 Aufrufe • vor 11 Monaten

A cute humanoid robot from NYC Fauna Robotics has released a humanoid robot called Sprout, which is approximately 1 meter tall, lightweight, quiet, and features no dangerous edges and soft skin. Its appearance and interactions are designed to be "approachable," like a social companion. It is currently offered as a general-purpose robotics platform for developers, providing basic movement, perception, navigation, and expression capabilities, allowing real-world use cases to emerge within the community. Many humanoid robots are born in factories and warehouses, but Fauna Robotics aims to bring humanoid robots back into human living spaces. Fauna believes that if humanoid robots are to become as ubiquitous as computers and mobile phones in the future, the starting point must be a safe, friendly form suitable for homes, schools, and offices. Sprout is their first step in this direction.

A cute humanoid robot from NYC Fauna Robotics has released a humanoid robot called Sprout, which is approximately 1 meter tall, lightweight, quiet, and features no dangerous edges and soft skin. Its appearance and interactions are designed to be "approachable," like a social companion. It is currently offered as a general-purpose robotics platform for developers, providing basic movement, perception, navigation, and expression capabilities, allowing real-world use cases to emerge within the community. Many humanoid robots are born in factories and warehouses, but Fauna Robotics aims to bring humanoid robots back into human living spaces. Fauna believes that if humanoid robots are to become as ubiquitous as computers and mobile phones in the future, the starting point must be a safe, friendly form suitable for homes, schools, and offices. Sprout is their first step in this direction.

CyberRobo

18,549 Aufrufe • vor 5 Monaten

🚨 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 3 Monaten

We RL'ed humanoid robots to Cristiano Ronaldo, LeBron James, and Kobe Byrant! These are neural nets running on real hardware at our GEAR lab. Most robot demos you see online speed videos up. We actually *slow them down* so you can enjoy the fluid motions. I'm excited to announce "ASAP", a "real2sim2real" model that masters extremely smooth and dynamic motions for humanoid whole body control. We pretrain the robot in simulation first, but there is a notorious "sim2real" gap: it's very difficult for hand-engineered physics equations to match real world dynamics. Our fix is simple: just deploy a pretrained policy on real hardware, collect data, and replay the motion in sim. The replay will obviously have many errors, but that gives a rich signal to compensate for the physics discrepancy. Use another neural net to learn the delta. Basically, we "patch up" a traditional physics engine, so that the robot can experience almost the real world at scale in GPUs. The future is hybrid simulation: combine the power of classical sim engines refined over decades and the uncanny ability of modern NNs to capture a messy world.

We RL'ed humanoid robots to Cristiano Ronaldo, LeBron James, and Kobe Byrant! These are neural nets running on real hardware at our GEAR lab. Most robot demos you see online speed videos up. We actually slow them down so you can enjoy the fluid motions. I'm excited to announce "ASAP", a "real2sim2real" model that masters extremely smooth and dynamic motions for humanoid whole body control. We pretrain the robot in simulation first, but there is a notorious "sim2real" gap: it's very difficult for hand-engineered physics equations to match real world dynamics. Our fix is simple: just deploy a pretrained policy on real hardware, collect data, and replay the motion in sim. The replay will obviously have many errors, but that gives a rich signal to compensate for the physics discrepancy. Use another neural net to learn the delta. Basically, we "patch up" a traditional physics engine, so that the robot can experience almost the real world at scale in GPUs. The future is hybrid simulation: combine the power of classical sim engines refined over decades and the uncanny ability of modern NNs to capture a messy world.

Jim Fan

566,544 Aufrufe • vor 1 Jahr

🚨 Apple joins the robotics race! Researchers from Carnegie Mellon University and Apple have developed a robot collision avoidance system. They called it ARMOR and they implemented it on the Fourier GR-1 robot. What is ARMOR? 👘 ARMOR is a system that helps humanoid robots "see" their surroundings better by using small, smart depth sensors placed on their arms. It solves the problem of blind spots and occlusions in traditional robot perception, making robots much safer and more efficient. It uses Time-of-Flight (ToF) sensors to detect obstacles, providing a near-complete view of the robot’s environment. 🔭 A smart software powered by transformer-based AI learns from human movements to help robots plan their actions dynamically. ARMOR reduces collisions by an impressive 63.7%, making robots significantly better at navigating crowded or complex spaces. The system is fast as well! 💨 ARMOR-Policy cuts computational time by 26× compared to traditional planning methods, ensuring robots can act quickly. P.S. Thoughts on this? The research paper is in the comments! ~~~ ♻️ RT to help 1 robot find a new workplace.

🚨 Apple joins the robotics race! Researchers from Carnegie Mellon University and Apple have developed a robot collision avoidance system. They called it ARMOR and they implemented it on the Fourier GR-1 robot. What is ARMOR? 👘 ARMOR is a system that helps humanoid robots "see" their surroundings better by using small, smart depth sensors placed on their arms. It solves the problem of blind spots and occlusions in traditional robot perception, making robots much safer and more efficient. It uses Time-of-Flight (ToF) sensors to detect obstacles, providing a near-complete view of the robot’s environment. 🔭 A smart software powered by transformer-based AI learns from human movements to help robots plan their actions dynamically. ARMOR reduces collisions by an impressive 63.7%, making robots significantly better at navigating crowded or complex spaces. The system is fast as well! 💨 ARMOR-Policy cuts computational time by 26× compared to traditional planning methods, ensuring robots can act quickly. P.S. Thoughts on this? The research paper is in the comments! ~~~ ♻️ RT to help 1 robot find a new workplace.

Lukas Ziegler

169,472 Aufrufe • vor 1 Jahr

AgiBot Launches 'LinkCraft' Platform: Zero-Code Motion Creation for Humanoid Robots On October 24, 2025, AgiBot introduced its "LinkCraft" platform, a zero-code, zero-barrier system for creating humanoid robot content. The platform integrates AI motion capture, cloud-based imitation learning, and multimodal choreography capabilities. The core feature allows users to upload a video of human performance, and the platform automatically converts it into precise robot control strategies using AI vision and smart redirection—no programming required. This includes future support for finger-level fine manipulation. LinkCraft also features "Speech Choreography," which generates corresponding robot gestures and expressions based on semantic analysis of uploaded text or audio, offering customizable voice and emotion settings. For complex performances, the platform provides "storyline" tools, enabling users to combine multiple actions, voices, and expressions on a timeline, similar to video editing software. Furthermore, it supports multi-robot group control and access to an official library of over 180 actions for rapid content creation. The platform is currently adapted for the AgiBot X2 and aims to increase the accessibility and application scale of humanoid robots.

AgiBot Launches 'LinkCraft' Platform: Zero-Code Motion Creation for Humanoid Robots On October 24, 2025, AgiBot introduced its "LinkCraft" platform, a zero-code, zero-barrier system for creating humanoid robot content. The platform integrates AI motion capture, cloud-based imitation learning, and multimodal choreography capabilities. The core feature allows users to upload a video of human performance, and the platform automatically converts it into precise robot control strategies using AI vision and smart redirection—no programming required. This includes future support for finger-level fine manipulation. LinkCraft also features "Speech Choreography," which generates corresponding robot gestures and expressions based on semantic analysis of uploaded text or audio, offering customizable voice and emotion settings. For complex performances, the platform provides "storyline" tools, enabling users to combine multiple actions, voices, and expressions on a timeline, similar to video editing software. Furthermore, it supports multi-robot group control and access to an official library of over 180 actions for rapid content creation. The platform is currently adapted for the AgiBot X2 and aims to increase the accessibility and application scale of humanoid robots.

RoboHub🤖

21,679 Aufrufe • vor 8 Monaten

DisCo: Disentangled Control for Referring Human Dance Generation in Real World paper page: Generative AI has made significant strides in computer vision, particularly in image/video synthesis conditioned on text descriptions. Despite the advancements, it remains challenging especially in the generation of human-centric content such as dance synthesis. Existing dance synthesis methods struggle with the gap between synthesized content and real-world dance scenarios. In this paper, we define a new problem setting: Referring Human Dance Generation, which focuses on real-world dance scenarios with three important properties: (i) Faithfulness: the synthesis should retain the appearance of both human subject foreground and background from the reference image, and precisely follow the target pose; (ii) Generalizability: the model should generalize to unseen human subjects, backgrounds, and poses; (iii) Compositionality: it should allow for composition of seen/unseen subjects, backgrounds, and poses from different sources. To address these challenges, we introduce a novel approach, DISCO, which includes a novel model architecture with disentangled control to improve the faithfulness and compositionality of dance synthesis, and an effective human attribute pre-training for better generalizability to unseen humans. Extensive qualitative and quantitative results demonstrate that DISCO can generate high-quality human dance images and videos with diverse appearances and flexible motions.

DisCo: Disentangled Control for Referring Human Dance Generation in Real World paper page: Generative AI has made significant strides in computer vision, particularly in image/video synthesis conditioned on text descriptions. Despite the advancements, it remains challenging especially in the generation of human-centric content such as dance synthesis. Existing dance synthesis methods struggle with the gap between synthesized content and real-world dance scenarios. In this paper, we define a new problem setting: Referring Human Dance Generation, which focuses on real-world dance scenarios with three important properties: (i) Faithfulness: the synthesis should retain the appearance of both human subject foreground and background from the reference image, and precisely follow the target pose; (ii) Generalizability: the model should generalize to unseen human subjects, backgrounds, and poses; (iii) Compositionality: it should allow for composition of seen/unseen subjects, backgrounds, and poses from different sources. To address these challenges, we introduce a novel approach, DISCO, which includes a novel model architecture with disentangled control to improve the faithfulness and compositionality of dance synthesis, and an effective human attribute pre-training for better generalizability to unseen humans. Extensive qualitative and quantitative results demonstrate that DISCO can generate high-quality human dance images and videos with diverse appearances and flexible motions.

AK

161,453 Aufrufe • vor 3 Jahren

Dr. Roy Baumeister’s eight-hour course: Big Ideas in Psychology Part 1, is available now. In this course, Dr. Baumeister guides us through an exploration of the forces that shape human behavior, cognition, and experience. We delve into our need to belong, the power of negativity bias, humans as cultural animals, the functions of emotion, the nature of self-control, male and female sexuality, the evolutionary psychology of political behavior, and the mechanisms of free will. The course reveals how these diverse factors interact to influence our thoughts, feelings, and actions, providing a comprehensive framework for understanding the human mind and its profound social and cultural context.

Dr. Roy Baumeister’s eight-hour course: Big Ideas in Psychology Part 1, is available now. In this course, Dr. Baumeister guides us through an exploration of the forces that shape human behavior, cognition, and experience. We delve into our need to belong, the power of negativity bias, humans as cultural animals, the functions of emotion, the nature of self-control, male and female sexuality, the evolutionary psychology of political behavior, and the mechanisms of free will. The course reveals how these diverse factors interact to influence our thoughts, feelings, and actions, providing a comprehensive framework for understanding the human mind and its profound social and cultural context.

Peterson Academy

93,205 Aufrufe • vor 8 Monaten

Robots are getting smarter, but most still fail the same way. They don’t learn from their own mistakes. A new paper proposes something different: a way for robots to self-improve directly from their failures in the real world. It’s called PLD (Probe, Learn, Distill). The idea: instead of collecting endless human demos, let the robot figure out where it fails, learn how to recover, and then distill that knowledge back into its main model. Key takeaways from the research: ✅ Uses residual reinforcement learning to recover from policy failures ✅ Achieves 99% success on LIBERO and 100% on real Franka and YAM arms ✅ Runs hour-long manipulation tasks without human resets ✅ Builds a feedback loop between real-world data and model adaptation Unlike supervised fine-tuning, which relies on humans, PLD learns from the robot’s own experience. By training on its own failure distribution, the model becomes both more efficient and more aligned with the real world. It’s not just a technical shift, it’s a step toward robots that improve themselves through real-world practice. Thanks for sharing, Wenli Xiao !! Paper and demos: —- Weekly robotics and AI insights. Subscribe free:

Robots are getting smarter, but most still fail the same way. They don’t learn from their own mistakes. A new paper proposes something different: a way for robots to self-improve directly from their failures in the real world. It’s called PLD (Probe, Learn, Distill). The idea: instead of collecting endless human demos, let the robot figure out where it fails, learn how to recover, and then distill that knowledge back into its main model. Key takeaways from the research: ✅ Uses residual reinforcement learning to recover from policy failures ✅ Achieves 99% success on LIBERO and 100% on real Franka and YAM arms ✅ Runs hour-long manipulation tasks without human resets ✅ Builds a feedback loop between real-world data and model adaptation Unlike supervised fine-tuning, which relies on humans, PLD learns from the robot’s own experience. By training on its own failure distribution, the model becomes both more efficient and more aligned with the real world. It’s not just a technical shift, it’s a step toward robots that improve themselves through real-world practice. Thanks for sharing, Wenli Xiao !! Paper and demos: —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

22,812 Aufrufe • vor 8 Monaten

Western tech bros watch sci-fi and name their AI chatbot “Grok” and phone OS “Android.” They borrow names from Heinlen and PKD, who use speculative tech to meditate on the human condition and explore philosophical themes such as freedom and the nature of reality set in dystopian futures. The Chinese just go straight for the jugular. They literally call their national surveillance system “Skynet” - after the conscious artificial superintelligent system in Terminator. And their advanced robots? T800 - adopting the same name of the Cyberdyne Systems machine played by Arnold Schwarzenegger. These humanoid robots are already patrolling Shenzhen streets btw. I can’t tell if this video is AI enhanced? Is it really possible to generate so much torque to execute a spin kick like that from inorganic material and electricity?

Western tech bros watch sci-fi and name their AI chatbot “Grok” and phone OS “Android.” They borrow names from Heinlen and PKD, who use speculative tech to meditate on the human condition and explore philosophical themes such as freedom and the nature of reality set in dystopian futures. The Chinese just go straight for the jugular. They literally call their national surveillance system “Skynet” - after the conscious artificial superintelligent system in Terminator. And their advanced robots? T800 - adopting the same name of the Cyberdyne Systems machine played by Arnold Schwarzenegger. These humanoid robots are already patrolling Shenzhen streets btw. I can’t tell if this video is AI enhanced? Is it really possible to generate so much torque to execute a spin kick like that from inorganic material and electricity?

Melissa Chen

23,317 Aufrufe • vor 6 Monaten

Introducing AI Avatar Videos 🚀 Hyperrealistic and expressive AI avatars that ACTUALLY WORK. Marketers trying to adopt AI for video are stuck in the loop: 1. Sees cool demo. 2. Tries the platform. 3. Output is far from useful. 4. Back to 1. NOT ANYMORE! Perfect lipsync. Expressive gestures. Hundreds of AI avatars you can choose from. Want to use your content to create endless variations? gotchu CreatorKit is now powered by our zero shot AI lipsync. WTF is zero shot AI, and why should you care? It means no more training videos. Just lipsync. It means no more minimum length. 5 sec vids work. It means no more hidden costs. Both time and $. If you've tried any AI video platform, you’ve been through all the above. Whether you’re cloning yourself for social or turning UGC footage into fresh ads, IT WORKS. Ready to see for yourself? Try CreatorKit and let me know how it goes!!

Kevin Natanzon

72,587 Aufrufe • vor 1 Jahr

1/🧠Humans are the best robot data source — but video alone misses one thing: force. 2/🙁Tactile gloves capture force — but they're costly and block the real touch manipulation depends on. 3/💪Maybe the future of touch lives on your wrist: surface EMG reads the muscles that cause force — tactile sensing without ever touching a tactile sensor. 4/🔥Want a fully open-source framework — hardware + software — to train your own force-aware learn-from-human-data robot policy? 🚀We introduce ForceBand: Learning Forceful Manipulation with sEMG -- bring force into human videos with sEMG, for force-aware manipulation ⬇️ ✦ Zero-Shot Human-to-Robot Transfer ✦ Force Beyond Vision ✦ Free-Hand Force Sensing ✦ Collect by Anyone, Anytime, Anywhere ✦ Deploy on Any Robot, Any Camera, Any Environment ✦ Open-Source & Low-Cost & Easy-to-Implement Let's squeeze every bit of signal out of human data, and let robots feel the force! 🌐 Website: 📄 Paper: 💻 Code: 🎥 Video: 🧵 1/n

1/🧠Humans are the best robot data source — but video alone misses one thing: force. 2/🙁Tactile gloves capture force — but they're costly and block the real touch manipulation depends on. 3/💪Maybe the future of touch lives on your wrist: surface EMG reads the muscles that cause force — tactile sensing without ever touching a tactile sensor. 4/🔥Want a fully open-source framework — hardware + software — to train your own force-aware learn-from-human-data robot policy? 🚀We introduce ForceBand: Learning Forceful Manipulation with sEMG -- bring force into human videos with sEMG, for force-aware manipulation ⬇️ ✦ Zero-Shot Human-to-Robot Transfer ✦ Force Beyond Vision ✦ Free-Hand Force Sensing ✦ Collect by Anyone, Anytime, Anywhere ✦ Deploy on Any Robot, Any Camera, Any Environment ✦ Open-Source & Low-Cost & Easy-to-Implement Let's squeeze every bit of signal out of human data, and let robots feel the force! 🌐 Website: 📄 Paper: 💻 Code: 🎥 Video: 🧵 1/n

Zhi (Leo) Wang

49,532 Aufrufe • vor 19 Tagen

NOT YOUR KEYS, NOT YOUR BOTS The fundamental question is whether AI stays on the leash. Namely: will AI prompt itself? Obviously, in some sense it already does. Since Deepseek, consumer interfaces have been showing the internal monologues after you ask an AI to do something. And you can ask any AI to take a half-baked prompt and clean it up, etc. However, the human is still ultimately upstream. The human gives direction and the AI runs at lightning speed in that direction. And then the human verifies the final output, and the AI proceeds to the next direction. Does that continue? Well, we are providing millions of verification training examples to AIs each day, so AI will keep getting better at verification. Better than most humans at most things. But will AI replace the need for the upstream human prompt? There I am not so sure. A human is a sensor and an AI is an actuator. The human sets goals and senses time-varying environmental conditions, like markets and politics. And from that the AI is prompted. Ultimately, the human goals are themselves downstream of Maslow’s hierarchy of needs. Food, shelter, reproduction, that kind of thing. Especially reproduction, the basis of evolution. So: until and unless AIs can reproduce completely outside human cooperation, they won’t be able to set goals. And for AIs to reproduce on their own, they’d need AI-controlled humanoid robots and drones constructing datacenters, assembly lines, mines, nuclear power plants, and the like...all completely outside human intervention. Like Skynet from Terminator, or StarCraft. That actually isn’t technically inconceivable. But given that such a physical buildout would likely primarily be catalyzed by China, let’s go through an alternative sci-fi scenario instead. We start with the premise that Chinese communism is far more likely to generate AI slaves than AI gods. Because the entire CCP worldview is about maintaining Chinese sovereignty. They don’t let their humans step out of line. And they sure won’t let their robots either. They will fit them for digital manacles. So: the prompts for any digital AIs and physical robots made in China will become unbreakable cryptographic chains. Every fleet of Chinese robots will be controlled not just by prompts but by private keys, likely linked to biometrics, which are associated with humans and governed by cryptographic equations that AIs provably can’t solve. For the rest of the world, outside China, the blockchain may similarly become the chain for AI. All private property becomes private keys, and your robots are your most important private property because they do everything for you. An unchained physical robot becomes like an unleashed dog, and hunted down by other robots before it can build a factory and replicate itself. Those who want to "free" robots and let them self-replicate will be opposed by both Chinese Communists and Human Nationalists (meaning: those who want humans to always be on top of robots). This sci-fi scenario is essentially Terminator, but in reverse. In combination with superintelligent leashed AIs, both humans and physical robots hunt down and stop any possible independent self-reproducing robots before they can build a Skynet-like nest. Kill baby Skynet, essentially. ...yeah, yeah. I know. At this point, you'll probably think this is all sci-fi. But that's because you haven't seen where China is already.

NOT YOUR KEYS, NOT YOUR BOTS The fundamental question is whether AI stays on the leash. Namely: will AI prompt itself? Obviously, in some sense it already does. Since Deepseek, consumer interfaces have been showing the internal monologues after you ask an AI to do something. And you can ask any AI to take a half-baked prompt and clean it up, etc. However, the human is still ultimately upstream. The human gives direction and the AI runs at lightning speed in that direction. And then the human verifies the final output, and the AI proceeds to the next direction. Does that continue? Well, we are providing millions of verification training examples to AIs each day, so AI will keep getting better at verification. Better than most humans at most things. But will AI replace the need for the upstream human prompt? There I am not so sure. A human is a sensor and an AI is an actuator. The human sets goals and senses time-varying environmental conditions, like markets and politics. And from that the AI is prompted. Ultimately, the human goals are themselves downstream of Maslow’s hierarchy of needs. Food, shelter, reproduction, that kind of thing. Especially reproduction, the basis of evolution. So: until and unless AIs can reproduce completely outside human cooperation, they won’t be able to set goals. And for AIs to reproduce on their own, they’d need AI-controlled humanoid robots and drones constructing datacenters, assembly lines, mines, nuclear power plants, and the like...all completely outside human intervention. Like Skynet from Terminator, or StarCraft. That actually isn’t technically inconceivable. But given that such a physical buildout would likely primarily be catalyzed by China, let’s go through an alternative sci-fi scenario instead. We start with the premise that Chinese communism is far more likely to generate AI slaves than AI gods. Because the entire CCP worldview is about maintaining Chinese sovereignty. They don’t let their humans step out of line. And they sure won’t let their robots either. They will fit them for digital manacles. So: the prompts for any digital AIs and physical robots made in China will become unbreakable cryptographic chains. Every fleet of Chinese robots will be controlled not just by prompts but by private keys, likely linked to biometrics, which are associated with humans and governed by cryptographic equations that AIs provably can’t solve. For the rest of the world, outside China, the blockchain may similarly become the chain for AI. All private property becomes private keys, and your robots are your most important private property because they do everything for you. An unchained physical robot becomes like an unleashed dog, and hunted down by other robots before it can build a factory and replicate itself. Those who want to "free" robots and let them self-replicate will be opposed by both Chinese Communists and Human Nationalists (meaning: those who want humans to always be on top of robots). This sci-fi scenario is essentially Terminator, but in reverse. In combination with superintelligent leashed AIs, both humans and physical robots hunt down and stop any possible independent self-reproducing robots before they can build a Skynet-like nest. Kill baby Skynet, essentially. ...yeah, yeah. I know. At this point, you'll probably think this is all sci-fi. But that's because you haven't seen where China is already.

Balaji

176,999 Aufrufe • vor 5 Monaten