AI model
Nvidia's platform of generative world foundation models and data-curation tools for training physical AI, robotics, and autonomous vehicle systems.
AWS released an open-source Physical AI Toolchain that joins four AWS services and four NVIDIA tools into one simulation-to-robot pipeline. It handles the plumbing between stages, though Interesting Engineering notes it cannot guarantee a simulation-trained model works on a real factory floor.
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AMD is buying Fei-Fei Li's World Labs for about $8.2 billion and making Li its chief scientist. The chipmaker says workloads like the lab's will shape its chip roadmap, a claim that matters most to teams training robots in simulation.
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The venue says more than the memorandum did. Humanoid margins get decided at the motion-data layer, and that is where the two companies are meeting.
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Skild says a single video demonstration teaches its S1 model an unseen ten-minute task with no weight updates. The accuracy figure published alongside that work is 66 percent per manipulation step.
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A Cambridge start-up says it trained walking and grasping in minutes. Its co-founder and Nvidia's robotics product director both put the current limit at fine dexterity and multi-step tasks like fill and pour.
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The Verge's reviewer has spent years living with home robots, and ahead of IFA's humanoid catwalk she argues the coordinating brain matters more than the body, after none of the humanoids at CES could open her laundry detergent.
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Two million Blackwell Ultra and Rubin parts, booked five months after a one million commitment. Custom silicon did not substitute for Nvidia; it added to the bill.
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Unitree's $66 billion valuation lost nearly half its value in a week, and robot brains still lack the data to justify the hype.
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LG Electronics says it will train on 100,000 hours of robot data inside the year at its Seoul DataFactory. The target turns a chairman-level MOU into a fleet purchase and a floor plan.
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