ShengShu’s Vidar makes humanoid robot training faster and cheaper

One of the biggest hurdles in developing humanoid robots is the sheer amount of training data required. Teaching machines to act like humans demands massive video datasets. Collecting that data is expensive, time-consuming and difficult to scale. This challenge has slowed progress toward making robots useful in everyday environments such as homes, hospitals and offices.

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CHINA LAUNCHES CENTER TO TRAIN 100-PLUS HUMANOID ROBOTS SIMULTANEOUSLY

Vidar by ShengShu transforms humanoid robot training

ShengShu Technology has introduced Vidar, short for Video Diffusion for Action Reasoning. Instead of relying solely on endless hours of physical-world data, Vidar generates synthetic training environments from just a small amount of real video. By blending real data with AI-generated video, Vidar makes training more efficient, scalable and affordable.

Vidar uses video to train robots to perform real-world tasks. (Vidar)

How Vidar uses AI video to speed up robot training

Vidar works by decoupling perception from control. First, it uses ShengShu’s Vidu video model to learn from both real and synthetic videos. Then, a task-agnostic system called AnyPos translates that knowledge into motor commands for robots. This modular setup allows for faster training and easier deployment across different types of robots.

Unlike traditional methods that require robots to physically interact with the world to learn, Vidar can simulate complex, lifelike scenarios virtually. Remarkably, it only needs about 20 minutes of training data, between 1/80 and 1/1200 of what leading models require. That efficiency makes it possible to scale robot training to levels never seen before.

CHINESE TECH FIRM SHARES ROBOT TRAINING SECRETS WITH THE WORLD

Vidar’s real-world replay and deployment with video model (Vidar)

Real-world applications of Vidar in humanoid robots

Vidar is more than just a research tool. Its design means robots can adapt quickly to new tasks and environments. That could unlock real-world applications in eldercare, home assistance, healthcare, and smart manufacturing. By bridging the gap between simulation…