Robotics is a data problem. Today, we’re partnering with... ABB Robotics, Universal Robots, and NVIDIA Robotics to deploy the Skild Brain across real-world industries from manufacturing to factory lines. This will help us build the world’s biggest data flywheel for physical AI.show more

America's leading robotics companies are powering the next wave... of reindustrialization. 🤖 Agility, Amazon robotics, Figure, and Skild AI are adopting the NVIDIA three-computer solution to deploy physical AI powered robotic fleets to bridge skills gaps, boost productivity, and improve safety across industries. #NVIDIAGTC Read the press release:show more

Robotics is obsessed with foundation models and humanoids. It’s... missing the most critical piece. One founder just raised $3M to build the “AWS for robots.” Fixing the silent bottleneck for most robotics startup: Data Infrastructure: 🧵show more

Physical AI is moving fast - from factory floors... to humanoid robots. 🤖 Join us at #NVIDIAGTC 2026 to see how NVIDIA’s open models, libraries, and growing ecosystem are accelerating robotics innovation. Check out our robotics sessions. ➡️show more

Stay tuned with NVIDIA Robotics folks, we’re expanding LeRobot’s... sim capabilities! I can train & teleop my SO-101 from real → sim, drop custom assets, and collect data from home (or HF office). finally making progress on the robotics dataset problem. Project launches soon 👀show more

Something big is happening in robotics - and it’s... hiding in plain sight. This post is not about dancing robots but in the data that powers them. Open robotics datasets have exploded this year, turning the field into a more scalable and collaborative ecosystem. In just two years, Hugging Face datasets grew from 11k to over 600k - and robotics is by far the fastest-growing segment. We went from 1k robotics datasets in 2024 to 27k in 2025! For comparison, text generation, the second-largest category, has only around 5k datasets in 2025. That gap is massive. Open datasets are important because robotics lives and dies by real-world robot data - video, actions, sensors, failures. By making this data easy to upload, reuse, and benchmark, researchers, startups, and large players are now releasing real-robot datasets that would have stayed locked inside labs just a few years ago. Major contributors include NVIDIA, LeRobot initiative, and a rapidly growing maker community. This surge is also enabled by cheaper video storage, better tooling, and an open-source AI culture now spilling into the physical world. And it really matters: open robotics data dramatically lowers entry barriers, accelerates learning-by-doing, and speeds up progress toward generalist and humanoid robots. Robotics won’t scale through hardware alone - but to a large extent through shared data. Viz below from AI World - link to the story and more viz/filters in comment.show more

Announcing our commercial partnership with Booster Robotics Booster builds... humanoid robot hardware, OS, and developer tools to make humanoid robots more affordable, reliable, and practical. The partnership centers on using simulation to multiply the value of real-robot data—expanding teleoperation demonstrations into scalable training data across diverse tasks and scenes. This joint effort powers sim-real co-training and foundation-model development, accelerating progress from hardware iteration to deployable robot policies. Together, we're building simulation‑powered data infrastructure for Physical AI — making scalable training data accessible to model developers and the broader robotics ecosystem.show more

🚨 Every revolution starts with a wild idea. We... built a Robotics Gym, where anyone can train real robots powered by on-device AI. Welcome to the world’s first AI & Robotics Gym 👇show more

SoftBank is reportedly in early talks to back a... massive $800M funding round for Munich-based Agile Robots, with a contribution of over $ 300M. The move signals a major escalation in Masayoshi Son's "brains and bodies" strategy to dominate physical AI infrastructure. Why this matters for the robotics industry: 🤖 The Flywheel: Agile Robots isn't just hardware. Founded by German Aerospace Center (DLR) alumni, they vertically integrate AI software with humanoids, warehouse automation, and robotic arms. 🧠 Frontier Ecosystems: Agile ONE was recently named a founding member of NVIDIA’s Cosmos Coalition and is deep in a research partnership with Google DeepMind to bring Gemini to the factory floor. 💰 The Capital Race: Global investment in robotics more than tripled in 2025. SoftBank is pairing this hardware play with its recent $1.4B investment in Skild AI and its $5.4B acquisition of ABB Robotics. While both companies have declined to comment on the early-stage talks, the deal highlights a furious shift toward deploying foundational AI in physical manufacturing and logistics.show more

NVIDIA is advancing graphics and simulation with agentic and... physical AI at #SIGGRAPH2026. From open models to real-time simulation, AI and graphics breakthroughs are transforming media, content creation, and robotics. Read the latest announcements. 👇show more

All robots need intelligence 🧠 Announcing #NVIDIA Isaac sim... GRID integration. Develop, simulate, and deploy robot AI without complex infrastructure, across consumer and commercial robots—humanoids, quadrupeds arms. Blog: #CES #Robot #AI #CES2025 NVIDIA NVIDIA Roboticsshow more

Two spacetimes, one data value chain >India: Workers’ headcams... record garment sewing egocentric data flows to AI/robotics companies. >China: Operators teleoperate humanoid robots in warehouses, sorting packages …validating the system ,collecting real-world training data.show more

2026 is also going to be the year of... data collection for robotics.show more

MasterBOT is officially integrating with NVIDIA Isaac Lab NVIDIA’s... robotics simulation platform built for developing and training autonomous machines This brings $BOT one step closer to powering the future of decentralized Robotics AIshow more

Sensei Robotics (YC S24) helps robotics companies generate high-quality... robotics training data at scale. Their platform collects human demonstration data at a tenth of the cost and twice the speed of current approaches.show more

OVER x Silencio We’re partnering with Silencio | Voice... Data for AI to add a new layer of data to the OVER mapping experience. Starting today, users can optionally capture real-world sound while creating their 3D maps inside the OVER app, and we seamlessly share the noise data with Silencio. This will soon allow mappers who capture both visuals and sound to also unlock additional rewards for their contribution. 🌎 We map physical locations around the world. 🌎 Silencio maps the world through sound. Together combining visual + audio signals , we’re enriching the foundation of Physical AI with deeper, multi-layered real-world data.show more

Physical AI gets better with broader real-world data. KGeN... captures human experiences at scale to help robots learn from them.show more

Robots don’t just need better brains. They need WAY... more real-world data. 🤖 And collecting high-quality dexterous robot data at scale is one of the hardest problems in physical AI. A fascinating approach is emerging: Wearable human demonstrations + structurally matched dexterous robots. Instead of humans directly teleoperating a robot, Chinese embodied AI startup X Square Robot's TwinDEX system captures the motion, contact, and visual information needed to train the robot — while keeping the data closer to the hardware that will actually execute the task. Early results show promising performance on tool use, fine manipulation, and complex contact-rich tasks. If this approach scales, it could change how we build real-world robotics datasets. The next frontier of physical AI might not be bigger models. It might be better data.show more

We’re filling the world with purpose-driven robots that benefit... humans and solve problems. Visit our brand new website to learn what makes us the future of robotics:show more