24 articles · Last covered
NVIDIA has agreed to acquire Hugging Face for $12.93 billion, bringing the open-source hub into its physical AI orbit just as Pollen Robotics launches the viral $399 Microduck.
LG has formalized a strategic partnership with NVIDIA to co-develop a bipedal humanoid robot, deploy wheel-based systems in U.S. factories, and build next-generation AI infrastructure.
A new collaboration brings NVIDIA Isaac GR00T 1.7, Isaac Teleop, and the upcoming Cosmos 3 world model directly into Hugging Face’s LeRobot ecosystem.
As the humanoid robotics industry grapples with the transition from lab demos to factory floors, NVIDIA has unveiled Halos for Robotics, a comprehensive safety system designed to move machines safely beyond the workcell.
At GTC Taipei, NVIDIA unveiled Cosmos 3, a breakthrough mixture-of-transformers omnimodel that transitions the robotics industry away from language-heavy VLA models toward native physical reasoning and action prediction.
Announced at GTC Taipei, the NVIDIA Isaac GR00T Reference Humanoid Robot bundles a Unitree H2 Plus chassis, Jetson Thor compute, and Sharpa Wave tactile hands into a unified open platform.
At Sequoia Capital’s AI Ascent, Jim Fan argued that robotics is speedrunning the LLM playbook, moving from video-based pre-training to autonomous self-improvement.
PSYONIC’s Ability Hand has become a native asset in NVIDIA Isaac Lab, introducing a "real-to-real" transfer pipeline that uses human-driven data to train dexterous robotic manipulation.
Texas Instruments integrates mmWave radar with NVIDIA Jetson Thor to bridge the gap between AI simulation and real-world deployment, targeting the "last mile" of robotic safety.
NVIDIA researchers have revealed EgoScale, a framework that leverages a massive 20,854-hour egocentric human dataset to train robots in complex, fine-grained manipulation with minimal robot-in-the-loop data.
NVIDIA has released SONIC, a generalist humanoid controller trained on 100 million frames of motion data, aiming to replace manual reward engineering with a scalable "System 1" foundation for whole-body movement.
NVIDIA GEAR Lab has released DreamDojo, an open-source world model pretrained on a massive 44,000-hour dataset of human egocentric videos. By using "latent actions" to bridge the gap between human and robot movement, the model achieves zero-shot generalization and real-time controllability for teleoperation and planning.
