Embodied AI
Astribot, a Chinese robotics startup, has unveiled SmoothRL, an online reinforcement learning framework designed to train policies during asynchronous execution – a growing reality for embodied AI deployments where inference and action run at different frequencies. The work, led by the company’s foundation model team, addresses a fundamental mismatch: when a robot receives new action chunks before previous ones finish, conventional RL that updates on entire chunks ends up crediting or blaming actions that were never actually executed. The framework partitions each action chunk into three regions – committed (already fixed), execution (actually performed), and discarded (overwritten by later inference) – and backpropagates gradients only through the execution region. This ensures that optimisation mirrors the robot’s real experience. SmoothRL also...
Fei-Fei Li’s startup World Labs has released Atlas, a next-generation world model billed as the first multimodal system capable of pixel-level camera-controllable image and video generation paired with native 3D scene reconstruction. Trained from scratch on text, image, video and 3D data, the so-called “omni model” unifies four distinct modalities within a single unified architecture. Its flagship innovation, termed “spatial context”, grounds each input image in a precise 3D coordinate space with explicit camera pose parameters. By treating geometric camera controls as native inputs, Atlas eliminates reliance on textual prompts to describe camera motion, letting users specify exact viewing angles and trajectories to generate up to 1440p-resolution videos with a maximum one-minute duration. World Labs frames the upgrade as letting...
A mysterious Chinese artificial intelligence team has released a series of uncut, one-take videos showing humanoid robots performing household tasks with fluid, human-like coordination, reigniting online speculation that embodied intelligence might be nearing a “ChatGPT moment.” The clips, which went viral last week, depict robots adapting to external physical disturbances while carrying a water glass, tidying a living room in a single long-horizon sequence, collaborating to smooth a bedsheet, and carrying multiple items at once – all without visible teleoperation, according to the developers. The underlying model, internally codenamed MVP – short for “Make Veritable People” – is designed to endow machines with physical reasoning and autonomous decision-making rather than probabilistic imitation, the team said in response to inquiries. In...
