Universal Robots and Scale AI Launch Imitation Learning System to Accelerate AI Model Training, Bridging the 'Lab-to-Factory' Gap
SAN JOSÉ, Calif., March 19, 2026 /PRNewswire/ -- Universal Robots (UR) this week unveiled the UR AI Trainer at GTC 2026. Developed in collaboration with Scale AI, the AI Trainer marks a shift as robots move from pre-programmed applications to fully AI-driven tasks.
"Our customers, ranging from large enterprises to AI research labs, are no longer just asking for AI features," said Anders Beck, VP of AI Robotics Products at Universal Robots. "They need a way to collect high-fidelity, synchronized robot and vision data to train AI models on the same robots they intend to deploy. Our AI Trainer is the industry's first direct lab-to-factory solution for AI model training."
Enabling AI-ready data capture
AI robotics training is often hindered by fragmented hardware and low-fidelity data capture. Today's training data is collected on research robots not suited for production environments, and many systems rely only on visual feedback, making delicate or contact-rich tasks difficult. "The AI Trainer directly addresses these barriers," said Beck.
"By utilizing our unique Direct Torque Control and force feedback features, we give developers direct influence over how the robot physically interacts with the world, training on the same robust hardware used in over 100,000 industrial deployments."
Scale AI partnership enables a flywheel of integrated robotics data
The UR AI Trainer lets human operators guide UR robots through tasks in a leader-follower setup, capturing high-quality synchronized multimodal data during real-time demonstrations, creating the structured datasets needed to train Vision-Language-Action (VLA). Running on UR's AI Accelerator platform, the AI Trainer combines collaborative industrial robots with Scale AI software to enable scalable data capture in production environments, supporting continuous optimization of physical AI systems.
"Universal Robots is a leader in industrial robotics, and its global footprint offers the ideal foundation for data capture and AI deployment," said Ben Levin, General Manager, Physical AI at Scale AI. "Together, we've created an integrated robotics data flywheel, allowing customers to train, deploy, and improve their AI models faster than ever before."
UR and Scale AI will release a large-scale industrial dataset collected on UR robots later this year.
Experience AI Trainer at GTC
Visitors to UR's GTC booth can guide two UR3e 'leader' robots providing haptic input to control two UR7e 'follower' robots. The setup enables visitors to perform advanced smartphone packaging with haptic feedback for imitation learning and VLA training, with demonstration data recorded in real time on Scale's stack and replayable directly on the AI Trainer.
The process of capturing robot training data for AI models is complemented by an embodied foundation model demo with Generalist AI and a haptics-based training demo with Haply Robotics. Read more on the UR website.
About
Universal Robots is a global leader in collaborative robotics (cobots), used across a wide range of industries. With over 100,000 cobots sold worldwide, our user-friendly platform is supported by intuitive PolyScope software, award-winning training, comprehensive services, and the world's largest cobot ecosystem, delivering innovation and choice to our customers. Universal Robots is part of Teradyne Robotics, a division of Teradyne (NASDAQ: TER), a leading supplier of automatic test equipment and advanced robotics technology.
Scale AI's mission is to develop reliable AI systems for the world's most important decisions. We provide high-quality data that powers the world's AI models, and we help enterprises and governments build, deploy, and oversee AI applications that create real impact. Through our research and Safety, Evaluations, and Alignment Lab (SEAL), we test models with rigorous benchmarks and novel research to help ensure AI is developed in ways people can trust. Founded in 2016, Scale is headquartered in San Francisco.
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