Introducing the OpenCyberGlove powered by NVIDIA technology! ๐
With 19 sensors, 200Hz sampling rate, and sub-5ms response time, this glove offers cutting-edge precision for motion capture. Experience top-tier performance like never before! ๐ฅ
#TechInnovation#MotionCapture
๐ Introducing CyberOriginโs Advanced Video Annotation Pipeline! Get precise, real-time video analysis that tags actions & underlying intentions with next-level accuracy and efficiency. #VideoAI#Annotation#CyberOrigin
CyberOrigin: Core supplier of robot training data for Tesla, NVIDIA, and OpenAI. While others collect basic visual data, we provide real physical interaction data that actually trains robots. #RoboticsData#AI#EmbodiedAI#DataCollection
CyberOrigin: The "water sellers" behind Tesla & NVIDIA's robot revolution. While everyone talks about humanoid robots, we're building the foundation that makes them possible. What we do: โข Supply training data to Tesla, NVIDIA, OpenAI โข 100K+ hours of real physical interaction
The most expensive ASMR video you'll ever watch ๐ธ OpenCyberGlove unboxing: ๐ Luxury packaging experience ๐ฌ 19 fiber-optic sensors ๐ฏ 200Hz sampling precision ๐ค Robot control capability Technology has never felt this satisfying #LuxuryTech#ASMR#Innovation#DataGlove#Te
The future of hand tracking is here! ๐
OpenCyberGlove breakthrough features:
๐ฏ19 fiber-optic sensors
โก Ultra-low 5ms latency
๐ 200Hz precision sampling
๐ค AI & robotics ready Revolutionizing human-machine interaction across industries! #TechBreakthrough#AI#Robotics
Introducing the OpenCyberGlove powered by NVIDIA technology! ๐
With 19 sensors, 200Hz sampling rate, and sub-5ms response time, this glove offers cutting-edge precision for motion capture. Experience top-tier performance like never before! ๐ฅ
#TechInnovation#MotionCapture
Unleash precision with the OpenCyberGlove! ๐ฅ
Ultra-lightweight, breathable design with 19 fiber-optic sensors, 0.1ยฐ resolution, and 200Hz sampling rate. IP54 rated for dust/splash resistance โ perfect for extended use in any environment! ๐
#TechInnovation#MotionCapture
Introducing the OpenCyberGlove! ๐ฅ
Weighing just 25g, this super-light, precise glove features 19 flex sensors, 120Hz sampling, and high degrees of freedom (DoF). Perfect for AR/VR and data collection with open-source SDK support! ๐ก
#TechInnovation#MotionCapture
Meet the OpenCyberGlove โ your advanced motion capture solution for robotics & AI! ๐ค
19 fiber-optic sensors, IMU integration, and real-time annotation tools. Precision at 0.1ยฐ resolution and 200Hz sampling rate for top-tier performance. ๐
#Robotics#AI#MotionCapture
Unlock the future of motion capture with the OpenCyberGlove! ๐ฅ
19 fiber-optic angle sensors, force sensors, strain gauges, and IMU for ultra-precise, low-latency tracking. Ideal for research, industry, and VR/AR. Modular and wearable design. ๐ช
#TechInnovation#MotionCapture
Revolutionizing motion capture with the OpenCyberGlove! ๐ฅ
Featuring 19 precision fiber-optic sensors for real-time data transmission, sub-5ms response time, and a 200Hz sampling rate. Perfect for immersive experiences. ๐
#MotionCapture#TechInnovation
๐ Ready to revolutionize your robotics projects?
๐ง Get OpenCyberGlove: [email protected] ๐ Documentation: https://t.co/1Y57KqMu84 ๐ป GitHub: https://t.co/gAHcHBPUY2 ๐19 flexible sensors across all joints
Let's build the future together! #TechSpecs#DataGlove#Innovation
๐ Introducing OpenCyberGlove by @CyberOrigin_AI - Revolutionary data collection redefined!
โจ Ultra-lightweight (25g) with 19 sensors
โก 120Hz precision for robotics & VR
๐ฎ Open-source SDK ready
๐ก Joint angle accuracy ยฑ2ยฐ
The future of dexterous manipulation is here!
๐จNew preprint ๐จ
Turning Down the Heat: A Critical Analysis of Min-p Sampling in Language Models
We examine min-p sampling (ICLR 2025 oral) & find significant problems in all 4 lines of evidence: human eval, NLP evals, LLM-as-judge evals, community adoption claims
1/8
What if an LLM could update its own weights?
Meet SEAL๐ฆญ: a framework where LLMs generate their own training data (self-edits) to update their weights in response to new inputs.
Self-editing is learned via RL, using the updated modelโs downstream performance as reward.
Uncut hour-long footage of Figure 02 autonomously transferring and flattening packages for a scanner down the line.
The robot is using Figureโs Helix model, a generalist VLA that now incorporates upgrades in temporal memory and force feedback.
Fei-Fei Li says real AI needs eyes. Not to look, but to move in 3D space.
Spatial intelligence gave animals agency, and machines will need it too.
And once AI can act in space, we can simulate limitless environments -- to train, explore, and create alongside them.