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One of the biggest obstacles Develop humanoid robots is the large amount of training data required. Teaching machines require large sets of video data, just like humans. Collecting data is expensive, time-consuming and difficult to scale. This challenge slows down the progress that makes robots useful in everyday environments such as houses, hospitals, and offices.
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China launches centers to train more than 100 humanoid robots at the same time
Vidar said its training method uses video to program robots in 20 minutes. (vidar)
Shengshu’s Vidar transforms humanoid robot training
Shengshu Technology Vidar has been introduced, the abbreviation for video diffusion for action reasoning. Vidar not only relies on endless physical world data, but generates a synthetic training environment from a small amount of real videos. By combining real data with AI-generated videos, 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 disconnects perception from control. First, it uses Shengshu’s Vidu video model to learn from real and synthetic videos. A task-independent system called AnyPOS then translates knowledge into motor commands for the robot. This modular setup allows faster training and easier deployment among different types of robots.
Unlike traditional methods that require robots to physically interact with the world to learn, Vidar can simulate almost complex, lifelike scenes. It is worth noting that it only takes about 20 minutes of training data, i.e. between 1/80 and 1/1200 of what is required for leading models. This efficiency makes it possible to extend robot training to levels never seen before.
Chinese technology companies share robot training secrets with the world
Real-world replay and deployment through video models of Vidar (vidar)
Real-world application of Vidar in humanoid robots
Vader is more than just a research tool. Its design means that robots can quickly adapt to new tasks and environments. This unlocks realistic applications of elderly care, family aid, healthcare and smart manufacturing industries. By bridging the gap between simulation and reality, Vidar positioned humanoid robots as practical helpers rather than futuristic concepts.
Humanoid robot performs medical procedures through remote control
Anypos-atara results and video replay to complete various manipulation tasks (vidar)
What does this mean to you
For consumers, Vidar brings the concept of a home or workplace robot helper closer to reality. Instead of waiting decades for robot maturity, scalable training can speed up deployment of daily setups. This could mean that robots provide you with chores, support for elderly care, and even help in a medical setting, earlier than expected.
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Kurt’s key points
Vidal is a milestone in the race toward practical humanoid robots. By integrating finite real data with generated videos, Shengshu has created a smarter and faster way to train physical AI. This approach can address cost, efficiency and scalability at once, which are three factors that have long restored robotics.
If it can help with daily tasks, would you welcome the humanoid robot at your home, or would the idea still be too futuristic? By writing to us, let us know Cyberguy.com.
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