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Brain-computer interfaces (BCI) & Robotics lack large-scale datasets. Fourier Robots is developing BCI-driven robotic rehabilitation training. Imagine a stroke patient thinks of moving a hand, and the robot detects the intent to guide the motion.

Rohan Paul

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91,159 次观看 • 5 个月前 •via X (Twitter)

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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.

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Alex Conley, who has a spinal cord injury, was the 2nd patient to undergo neurosurgery at Barrow to receive @Neuralink's N1 Implant as part of the PRIME Study. Now, also enrolled in CONVOY, Alex is the 1st to use the brain-computer interface (BCI) device to control a robotic arm.

Alex Conley, who has a spinal cord injury, was the 2nd patient to undergo neurosurgery at Barrow to receive @Neuralink's N1 Implant as part of the PRIME Study. Now, also enrolled in CONVOY, Alex is the 1st to use the brain-computer interface (BCI) device to control a robotic arm.

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1960s — first brain-computer interface experiments 1998 — first human BCI implant 2005 — paralyzed patient regains movement via BCI 2026 — furry tail, hands-free

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I set the world record for cursor control with a brain computer interface using my Neuralink brain implant! #Neuralink #bci #fyp

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German robotics company NEURA Robotics has created NEURA Gym: a large-scale, physical AI gym and training ground where hundreds of robots, including the humanoid 4NE-1, learn through real-world interactions. The company is collaborating with the Neuraverse ecosystem to create the world's largest repository of physical training data, promoting the application of humanoid robots.

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Straight out of a sci-fi movie! Shanghai robotics company Fourier (傅利叶) released a video showing how brain–computer interfaces and exoskeletons are used to sync data and train humanoid robots. Watching humans teach machines—honestly, it gives chills. Video from 顾捷傅利叶CEO Fourier Tuo Liu tphuang Zhang Heqing

Straight out of a sci-fi movie! Shanghai robotics company Fourier (傅利叶) released a video showing how brain–computer interfaces and exoskeletons are used to sync data and train humanoid robots. Watching humans teach machines—honestly, it gives chills. Video from 顾捷傅利叶CEO Fourier Tuo Liu tphuang Zhang Heqing

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Using monkey brain data to operate robotic arms! 🙉 Project Jenkins explores brain-computer interfaces by decoding neural activity into robotic movement and generating synthetic brain data from motion patterns. Using neural recordings from a macaque monkey named Jenkins, researchers developed models to decode brain signals into robotic arm movements and encode movement data into simulated neural activity. The project utilizes robotic arms and an interactive web console for real-time brain data generation from joystick inputs. The research paves the way for adaptive brain-computer interfaces by modeling brain activity more flexibly. Congrats to authors Dima Yanovsky, and Andrii Zahorodnii! 🦾

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The New England Journal of Medicine (NEJM) today published a peer-reviewed original paper with the results of a landmark clinical trial of our PRIMA brain-computer interface (BCI) retinal implant.

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China’s first humanoid training base, established by the National Humanoid Robot Innovation Center, began operations yesterday. “The training base is essentially a factory that produces data,” said Jiang Lei, chief scientist of the innovation center. The 50k sq. ft. training hub will launch with over a dozen tasks involving 100 robots from more than 10 companies and institutions, including AGIBOT and Fourier. The data gathered here will eventually be available to companies developing embodied AI models. By 2027, the Shanghai facility aims to scale to support 1,000 robots under training.

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Introducing FoundationMotion. A large-scale, video-derived motion annotation dataset & auto-labeling pipeline + advanced models for motion understanding. Fully open-source: code, datasets, and models, free to use and build on. Understanding motion is core to physical reasoning, yet today’s leading models still struggle with simple spatial actions like “turn right” or “move up” or “flip the toast” - mainly due to the lack of large, fine-grained motion datasets. We present FoundationMotion, a fully automated pipeline that: • detects & tracks objects in videos • extracts trajectories • uses LLMs + frames to generate rich motion captions & QA pairs → creating large-scale, high-quality motion datasets at scale. After fine-tuning the open-source models Qwen and NVILA on our annotations, these models now outperform the closed-source Gemini-3-Flash and GPT-5.1 on spatial understanding tasks across autonomous driving, robotics, and everyday scenarios. 📜Paper: 🌐Webpage: 💻 Code: 🕸️Model: 📊 Dataset: 👉 Interactive Demo: Let’s move research forward together. FoundationMotion is also referred to as Wolf V2 🐺, the second chapter in the Wolf series:

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We asked Angus about the future of robotics and AI training. “I built an industrial-grade kinematic solver for 6 degrees of freedom motion, with full path planning and joint control." "You can stream AI model outputs into it, or run it like a traditional industrial robot." "The benefit of that is all of that information you can stream and record from those joints… you can use that as the training data." "Frankly, moving a robot with a lever is really crap data for training robots. But this gives you smooth, high-quality motion, without needing two robots.”

We asked Angus about the future of robotics and AI training. “I built an industrial-grade kinematic solver for 6 degrees of freedom motion, with full path planning and joint control." "You can stream AI model outputs into it, or run it like a traditional industrial robot." "The benefit of that is all of that information you can stream and record from those joints… you can use that as the training data." "Frankly, moving a robot with a lever is really crap data for training robots. But this gives you smooth, high-quality motion, without needing two robots.”

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NVIDIA just announced EgoScale 🤖🧠 NVIDIA Research has uncovered a log-linear scaling law for robot dexterity by pretraining VLA models on over 20,000 hours of egocentric human video This massive dataset is 20 times larger than previous efforts and proves that robot intelligence follows a predictable path: the more human data, the lower the loss The secret is a simple recipe combining large-scale human pretraining with a small amount of aligned human-robot mid-training to bridge the gap In testing, this method boosted the average success rate by 54% on a 22-DoF robotic hand compared to policies built without pretraining EgoScale also enables one-shot task adaptation and works across different hardware, suggesting that human motion is a universal motor prior for robots Website: Paper: Source: NVIDIA Research #Robot #Humanoid #Robotics #AI #EmbodiedAI #PhysicalAI #NVIDIA #EgoScale #GR00T

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