AI that speaks, sounds, and moves.

Clinical and bio workflows punish fragile models quickly. - Agentic robotics places a large language model (LLM) agent in the robot control loop, where it composes perception, motion, and vision-language-action (VLA) tools under the guidance of a memory and...

Clinical and bio workflows punish fragile models quickly. - How should demonstration quality be used during vision-language-action (VLA) pretraining to improve performance after target-task fine-tuning?

Clinical and bio workflows punish fragile models quickly. - Long-horizon agents have drawn growing attention for their ability to work autonomously -- from hours to days -- on economically valuable tasks, a capability essential to automated discovery and...

Clinical and bio workflows punish fragile models quickly. - Bringing general-purpose agents into the physical world calls for an executable representation of physical intelligence.

Although end-to-end driving policies have advanced rapidly, the accumulated closed-loop errors, especially in unseen scenarios, can push vehicles into states from which the same policy struggles to recover. Why it matters Clinical and bio workflows punish fragile models quickly.

Clinical and bio workflows punish fragile models quickly. - How can we build an agent that thinks beyond human language, yet still acts through it in the external environment?

Clinical and bio workflows punish fragile models quickly. - Repetition counting requires identifying and enumerating action cycles over time.

Clinical and bio workflows punish fragile models quickly. - Robot policies are expected to generalize across deployment environments, including variations in the robot itself: cameras are bumped and remounted, calibrations drift, controllers run at different...

With the rapid development of multimodal large language models (MLLMs), evaluating their video understanding capabilities has become increasingly important. Why it matters Clinical and bio workflows punish fragile models quickly.

Given the same initial observation and low-level action sequence, WorldOracle asks whether a predicted rollout reproduces what happens in the real world, including physical consequences and task-state transitions. Why it matters Clinical and bio workflows punish fragile models quickly.