Azernews.Az

by Alimat Aliyeva

South Korea’s LG Electronics announced on Tuesday that it plans to deepen its collaboration with Nvidia in the field of robotics after hosting executives from the U.S. chipmaker at its new data factory, which is currently under construction in Seoul.

LG said the facility is expected to become fully operational by the end of 2026. It will include dedicated training areas where robots can practice a wide range of tasks and collect data through physical interaction with their surroundings.

According to LG, data gathered at the new facility will be integrated with Nvidia’s robotics software ecosystem, where it can be augmented and combined with synthetic data to create high-quality datasets for training robots.

LG expects the amount of training data collected and generated through the facility to reach 100,000 hours by the end of this year. The company says this would be equivalent to roughly 12 years of continuous data.

The technology will be used to further improve LG’s Robot Foundation Model, an AI system designed to help robots understand their environment, learn new tasks and perform a wider variety of actions.

The partnership highlights a broader shift in the robotics industry, where companies are increasingly focusing not only on hardware but also on the massive amounts of data needed to train intelligent machines. Much like generative AI systems require enormous datasets to improve their performance, next-generation robots need real-world and simulated experiences to learn how to operate safely and efficiently.

Interestingly, synthetic data could become particularly important in this process. Instead of making robots physically repeat millions of tasks, companies can use virtual environments to generate additional training scenarios, potentially saving both time and money.

LG’s investment also reflects the growing competition to develop so-called humanoid and general-purpose robots. If successful, such machines could eventually be used in factories, warehouses and other environments where they need to perform multiple tasks rather than a single repetitive operation.