This humanoid robot plans to do housework together with domestic workers.

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At present, the embodied intelligence sector is facing an awkward reality: robots performing spectacular backflips on stage, but they may not even be able to autonomously put slippers back on the shoe rack.

It has become an industry consensus that data is the bottleneck restricting the evolution of robots.

To break this bottleneck, the industry urgently needs to seek interactive data from the real physical world.

Among the many application scenarios, the data generated by daily home life is undoubtedly one of the scenes with sufficient complexity and training value. The essence of the home environment is randomness, fragmentation, and constant change—for example, cats might jump onto tables at any time, carpets have varying friction, and scattered toys have no pattern at all.

This noisy and uncertain data is precisely the key training field for embodied intelligence to achieve generalization. But it is also a difficult territory for data acquisition, with the core barrier being privacy boundaries. Allowing a device packed with cameras and sensors into private spaces is tantamount to challenging the bottom line of public trust.

But the home scenario is also a difficult territory for data acquisition, with the core barrier being privacy boundaries. Allowing a device packed with cameras and sensors into private spaces is tantamount to challenging the bottom line of public trust.

Despite the high threshold of trust, robot companies have begun to explore "entering homes" to break through, in order to obtain real-world interactive data.

Recently, Variable Robot announced that its robot equipped with the new generation embodied intelligence base model WALL-B will enter real homes starting May 25.

Prior to this, Variable Robot partnered with 58.com to send robots equipped with the WALL-AS model into real homes to collaborate with cleaning staff.

In response to market concerns about privacy, Variable Robot's solution is edge-side image desensitization, authorization mechanism, and restriction of data use.

According to Variable Robot founder and CEO Wang Qian:

First, visual desensitization: the robot performs real-time mosaic processing of raw images on the device; the original images do not leave the device, and what the robot sees is scene data with personal features removed;

Second, transparent authorization: the device can only be turned on after the user actively presses the consent button; there is no "default consent," and if the user does not agree, the device does not start;

Third, purpose limitation: absolutely no sharing with third parties, the robot recognizes only one owner, and will immediately lock upon detecting suspicious instructions.

The new generation of robots equipped with the WALL-B model adopts an architecture based on the World Unified Model (WUM), which jointly trains vision, language, hearing, and actions from scratch in the same network, achieving "multi-modal input, multi-modal output."

The purpose of such a design is to eliminate transmission loss between modules, allowing the model to natively perceive gravity, friction, and other "worldviews" of the physical world, and to self-iterate in real failed interactions.

From entering homes to collect data to feedbacking data into the model, this commercial logic loop has theoretically been completed.

However, objectively speaking, the capabilities currently demonstrated by Variable Robot still fall short of true "home service." According to on-site observation by All Weather Technology, the robot's actions are very slow, for example, it takes two and a half minutes just to place three flowers.

Wang Qian frankly admits that the current model is still at the "intern" stage: it makes mistakes, needs remote assistance, and sometimes might put slippers in the kitchen or stop halfway through wiping a table to "think." But it can work non-stop 24 hours a day, becoming "smarter" each day due to newly generated data.

The capital push is supporting this long "internship period."

Variable Robot recently completed a nearly 2 billion RMB Series B round of financing led by Xiaomi Ventures, and previously gathered Meituan, Alibaba, and ByteDance among its investors.

With its backing of a star-studded list of shareholders, whether Variable Robot can set the "data flywheel" spinning is being closely watched.

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