TAG
#embodied-ai
Stories connected through a shared idea, actor, technology or theme.
Qiyuan puts personal robots on sale in ChinaQiyuan announced prices starting at 19,999 yuan for Q1 and 29,999 yuan for the T1 Pro, with deliveries scheduled from October 1. The company described the robots as foldable or transformable personal platforms and said it would provide SDK and hardware-development access.→Dongfeng schedules humanoid robots for factory workDongfeng’s chief engineer said Xiaodong would begin factory work in October and move to small-batch, limited-site trials by year-end. The automaker is targeting human-level capability by the end of 2027, which is a roadmap claim rather than demonstrated performance.→Faraday Future unveils nine embodied-AI robot configurationsThe company said the launch covered the Futurist, Master Mini and three FX Aegis configurations, alongside solutions for education, research, security and inspection. Faraday Future also said the Futurist was on sale and that the Master Mini would start at $9,990; independent evidence of deployment or capability was not provided.→Dynamic Creatures launches SnowJay platform for interactive character robotsDynamic Creatures said it is Boston Dynamics’ official entertainment and hospitality partner and is developing mobile robots that respond to people and changing environments. Its SnowJay platform combines perception, learning-based control, behavioural programming and character design.→Generalist raises another $200 million for robot foundation modelsAxios reported that Generalist raised around $200 million in a round led by 8VC, with the company’s federal filing disclosing the financing. Generalist builds models rather than robot hardware and was founded by alumni of Google DeepMind and Boston Dynamics.→HiFi-UMI makes robot-free demonstrations competitive with teleoperation in tested tasksThe report evaluates HiFi-UMI across three policy backbones and four bimanual tabletop tasks, finding success differences of -2.5, +3.1 and -0.6 percentage points against in-domain real-robot teleoperation baselines. It also reports 85% success on a precision-insertion task and lower offline action-prediction error with pretraining, while limiting the conclusions to the tested models, tasks and conditions.→