One question. Six robots. 🤖 At #NVIDIAGTC Taipei, we asked FOXCONN HON HAI TECHNOLOGY, Noble Machines, RLWRLD, Solomon AI and 3D Vision, TECHMAN ROBOT, and YUAN High-Tech to describe their robot in just a few words.
NVIDIA Robotics
Computer Hardware Manufacturing
Santa Clara, California 521,937 followers
Inspiring visionaries and developers to create the next gen of AI-driven robots and explore the world of physical AI.
About us
The NVIDIA Robotics platform accelerates the development of AI-driven robots, streamlining processes from design and simulation to deployment. It enables key functions like navigation, mobility, grasping, and vision, supporting robotics across industries such as manufacturing, agriculture, logistics, and healthcare.
- Website
-
https://www.nvidia.com/en-us/industries/robotics/
External link for NVIDIA Robotics
- Industry
- Computer Hardware Manufacturing
- Company size
- 10,001+ employees
- Headquarters
- Santa Clara, California
Updates
-
Flexible manufacturing is entering a new era at #Automate2026. Come join leaders from ABB Robotics, FANUC America Corporation, Universal Robots, and Inbolt to explore how robotics and AI are transforming automation across the factory floor. Learn more 🔗 https://nvda.ws/3RWquGv 🎤 Craig McDonnell | Managing Director, Business Line Industries, ABB Robotics Claude Dinsmoor | VP- Robotics Research & Development, FANUC America Anders Billesø Beck | VP, AI Robotics Products, Universal Robots Albane Dersy | Co-Founder and COO, Inbolt
-
-
If you are headed to #SIGGRAPH2026 in LA this July, check out NVIDIA Research’s MotionBricks work for both animation and robotics. 🤖 Learn about our presence: https://lnkd.in/gyEKPa8
One open model. 350,000+ motion clips. 15,000 FPS. MotionBricks from NVIDIA Research runs real-time character animation at scale, without hand-crafted transitions or fine-tuning. And yes, it works for robotics too. #SIGGRAPH2026 paper, demos + code: https://lnkd.in/gZs_fygZ
-
1 week, 2 cities, one clear signal: robotics is in full force 🤖 At #CVPR2026 and #ICRA2026, researchers and innovators across robotics, computer vision, generative AI, and embodied AI came together. From keynotes and research talks to posters, partner demos, and networking events, the momentum behind physical AI was on full display. Shoutout to the NVIDIA Research team and the broader research community for their incredible work. 🙌
-
-
What does it really take to scale humanoid robots from concept to reality? 🤖 At #Automate2026, join leaders from Agile Robots SE, Agility Robotics, NEURA Robotics, and Skild AI to discuss the journey from foundation models and digital twins to real-world deployment. More details 🔗 https://nvda.ws/4ek1Ln2 🎤 Speakers: Zhaopeng Chen | CEO & Founder, Agile Robots Pras Velagapudi | CTO, Agility David Reger | Founder & CEO, NEURA Robotics Deepak Pathak | CEO & Co-founder, Skild AI Amit Goel | Head of Robotics Ecosystem and Edge AI Product, NVIDIA
-
-
🎉 The Yocto Project is now officially supported on NVIDIA Jetson with JetPack 7.2, building on years of community work in meta-tegra, the layer that first brought the Yocto Project to the Jetson platform. Join Matt Madison and NVIDIA experts on Monday, June 15 at 10 AM PT to learn how meta-tegra became a trusted foundation for embedded Linux developers and what its evolution to official support means for building with NVIDIA Jetson.
Yocto Project on Jetson: From Community Project to Official NVIDIA Support
www.linkedin.com
-
How do delivery robots safely navigate busy city streets? 🤖 Join us and Coco this Wednesday at 11 AM PT for a behind-the-scenes look at how autonomous robots are developed and deployed, plus key lessons learned from real-world operations. Learn how simulation with NVIDIA Isaac Sim helps validate autonomy and scale safe, efficient operations in urban environments. 🎤 Brad Squicciarini and Bolei Zhou
How Urban Simulation is Building Better Autonomous Delivery
www.linkedin.com
-
NVIDIA Robotics reposted this
Last week at #NVIDIAGTC Taipei, we caught up with the physical AI community to hear what they were most excited about from the keynote and what they’re building next. Missed the keynote? Watch the replay 👉 https://nvda.ws/4gcg7rS
-
Attending #Automate2026? 🤔 Join us and our partners at North America’s largest robotics and automation event to explore what’s next in physical AI. Hear from industry leaders, attend special events, and experience live demos showcasing real-world applications.🦾 Learn about our presence: https://nvda.ws/4ex3lTA
-
NVIDIA Robotics reposted this
NitroGen just won CVPR Best Paper Honorable Mention! Feels like a full-circle moment: 4 years ago, MineDojo, our first Minecraft AI agent, took Outstanding Paper at NeurIPS. NitroGen is an open-source Foundation Agent that learns to act across 1000+ 2D and 3D virtual worlds. Each world is a physics simulation with its own rules, dynamics, and motor commands. We're on a quest for general-purpose embodied AI that masters not only real-world physics, but every possible physics across a multiverse of simulations. A surprising discovery: our GR00T N1.5 architecture, originally designed for robots, adapts almost effortlessly to worlds with wildly different mechanics. The recipe is simple and bitter-lesson-pilled: (1) a 40K+ hour, high-quality dataset of public in-the-wild play; (2) a highly capable foundation model for continuous motor control; (3) a Gym API that wraps any simulated environment to run rollouts. GR00T N1.5 learns to compress and map 40K hours of pixels to diverse actions. Humans are extraordinarily good at adapting to vastly different physics and rules - something that continues to elude our most advanced, trillion-scale LLMs. The more virtual worlds an agent can adapt to, the better it develops embodied reasoning, perception, and motor coordination. All critical pieces in the grand puzzle for robotics. During my PhD, a tiny neural net that played 50 Atari titles with 84×84 grayscale window was considered mind-blowing. OpenAI Five and AlphaStar then went superhuman, yet stayed brittle, overfit to one environment at a time. NitroGen is our shot at the next rung: a dataset, a benchmark, and a competent base model checkpoint for embodied *generalization*. NitroGen is only the beginning, and there's a long way to hill-climb on capabilities. We open-source *everything* for you to tinker: code, pretrained weights, the full action dataset, and a whitepaper with real details. Today, robotics is a superset of hard AI problems. Tomorrow, it might become a subset, a dot in the much larger latent space of embodied AGI. Then you just prompt and "ask for" a robot brain. Congrats to the co-first authors, Loic, Anas, and Guanzhi, and thanks to all the colleagues across multiple institutes for making NitroGen happen! Website: https://lnkd.in/geiNxkq9 Paper: https://lnkd.in/gmCBMBmV Code: https://lnkd.in/gRGDnnpy Pretrained model weights: https://lnkd.in/gNangU74 Action dataset: https://lnkd.in/gW36UJpy