Everyday Living Spaces Transformed into Robot Training Grounds

Deep News
08/23

At a talent apartment complex within Haidian District's AI Origin Community, a group of young professionals has turned their daily living quarters into a dedicated "training field" for robots. The question arises: why conduct experiments in an apartment setting? Traditional laboratories often lack sufficient space and offer monotonous backgrounds, making it difficult for robots to generalize learned skills to real-world scenarios.

Within these residential units, however, robots are tasked with making beds in the bedroom, preparing meals and pouring water in the kitchen, and cleaning in the bathroom. This authentic home environment provides a diverse range of data that helps train what could be described as a robot's "powerful brain." Of course, the experiments are far from smooth sailing. Wang Zeyuan, Executive Lead of the World Model at Shengshu Technology, notes that current embodied models are still immature, with success rates far from 100%. Incidents such as hitting obstacles during delicate operations or accidentally squashing tomatoes are common occurrences. Nevertheless, Wang and his team remain confident in their ability to optimize and iterate on the technology going forward.

The talent apartment initiative conveniently supports this type of experimental work. Li Chao, the Industrial Services Lead at the Beijing AI Origin Community, explains that what was originally just housing for corporate employees is now open to enterprises, universities, and research institutes. These groups can move in with minimal preparation to conduct data collection and model training. Robots can be brought in and put to work immediately, with water, electricity, and network costs fully covered. This approach is not only more cost-effective than lab-based data collection, but it also yields higher-quality data.

Looking ahead, mature models trained in this environment will eventually be applied back within the community itself. AI starts here, returns here, and ultimately extends into more people's daily lives.

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