Startup Rhoda AI unveils robot system trained on millions of videos to predict motion and act in real time outside labs.
Robotics startup Rhoda AI has emerged from stealth with a new approach to robot intelligence that it says can help machines operate reliably outside controlled laboratory settings. The company also announced it has raised $450 million in Series A funding to scale its technology and expand industrial deployments.
The system, called FutureVision, is built on a model architecture that predicts how the physical world will change and then converts those predictions into robot actions. Rhoda says the system can continuously observe its surroundings, forecast future states as video, act on those predictions, and repeat the process every few hundred milliseconds.Industrial robots today typically rely on pre-programmed paths and perform best in tightly structured environments. Even newer AI approaches such as vision-language-action models often struggle when conditions change. Unexpected objects, shifting layouts, or irregular workflows can cause robots to fail or require human intervention.Rhoda says its approach addresses this limitation by training robot models on internet-scale video data before refining them with robot-specific learning.Training robots on videoInstead of relying primarily on teleoperated robot demonstrations, Rhoda pre-trains its system using hundreds of millions of online videos. According to the company, this allows the model to learn patterns of motion, physics, and physical interactions before it ever controls a robot.The system is then fine-tuned with smaller amounts of real robot data so it can translate visual predictions into physical actions. Rhoda says the resulting architecture, which it calls a Direct Video Action model, allows robots to adapt to changing conditions while they are working.Unlike open-loop systems that generate a plan once and execute it without feedback, Rhoda’s model updates its actions continuously based on what it observes in the environment. The company says this closed-loop process helps robots maintain accuracy when conditions shift.The approach also reduces the amount of robot training data required. Rhoda says new tasks can often be learned with as little as ten hours of teleoperation data.Robots beyond lab environmentsThe company says its technology has already been tested in production environments where robots must deal with constantly changing materials and workflows.In one high-volume manufacturing evaluation, Rhoda reported that a robot system completed a component-processing workflow in under two minutes per cycle without human intervention, exceeding customer performance targets.“We believe the next era of robotics requires models that understand how the world moves – not just what it looks like or how it’s described in language,” said Jagdeep Singh, cofounder and CEO of Rhoda. “By learning from internet-scale video and operating in closed loop, our systems are designed to adapt to real-world variability in ways conventional approaches struggle to achieve. The goal is simple: robots that work in the real world, not just controlled lab settings.”Investors say the technology could expand automation into areas that have historically been difficult for machines.“In manufacturing, tasks with high variability have historically resisted automation. The real challenge isn’t solving it once, it’s delivering consistent, reliable output under real-world production conditions,” said Jens Wiese, managing partner at VC firm Leitmotif and former Volkswagen Group executive.Rhoda says the new funding will support further research and engineering work, industrial pilots, and expansion of its robotics team.The company says FutureVision will eventually serve as a foundation model that can be licensed to partners building robotic hardware and software platforms.
Automation Technology Futurevision Robotics Industrial Robotics Robot Control Systems Robot Foundation Models Robotics AI Video Predictive Robotics
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