On July 24, 2026, at the APEC Digital and AI Ministerial Meeting in Chengdu, China, Zibian Robot (自变量机器人) stood as the sole representative of China's embodied AI industry. Founder and CEO Wang Qian delivered a keynote on 'Developing AI for People's Livelihood,' sharing real-world deployments that move beyond lab demos.
Zibian was selected as one of only eight Chinese speakers and its robot-in-home project was included in the APEC Digital Empowerment Case Collection as the only embodied AI case serving people's livelihood. This recognition signals a shift: embodied AI is no longer just about impressive demos but about solving everyday problems.
Wang Qian made three concrete proposals: first, that APEC economies open more livelihood scenarios like home services, elderly care, healthcare, and logistics sorting for robot iteration; second, strengthen open-source collaboration on data standards, safety, and ethics; third, build talent pipelines with universities. These are not vague calls but actionable steps for the industry.
Zibian's edge lies in dual-track deployment. In homes, it partnered with 58到家 (58 Daojia) to launch robot-assisted housekeeping in Shenzhen, expanding to Beijing after serving over 1,000 households. Robots work alongside human cleaners, handling tasks like picking up trash—a simple act that profoundly impacts seniors with mobility issues. One elderly user hadn't bent down in two weeks before the robot arrived.
In industrial settings, Zibian deployed robots on a real logistics sorting line for a top Chinese logistics company. The robots handle diverse parcel sizes, weights, and materials, achieving 1,200+ items per hour with a return rate below 3%, running 24/7. This is not a pilot but a production-grade deployment.
Underpinning these capabilities is WALL-B, the world's first 'world unified model' architecture released in April 2026. It integrates vision, language, touch, action, and physics prediction into a single neural network, trained from scratch. WALL-B understands gravity, inertia, and friction, enabling zero-shot adaptation to novel scenes and continuous self-improvement.
For founders and operators, Zibian's APEC appearance offers three signals. First, embodied AI's commercial frontier is not in factories but in homes and logistics—high-mix, semi-structured environments. Second, the business model is clear: robots as augmenting labor, not replacing humans, in partnership with existing service platforms. Third, the technology moat is a unified world model that generalizes across tasks, not narrow vertical solutions.
Zibian's trajectory suggests that the winning strategy is to deploy early in messy real-world scenarios, iterate on data, and build a generalist brain. The company's focus on 'serving people's livelihood' is not just PR but a product thesis: robots must work where people actually need help.
Source: 雷峰网.