what is hy-embodied-rxbrain-1.0 fr?

Hy-Embodied-RxBrain-1.0, also called RxBrain, is a research model from Tencent Robotics X, Futian Laboratory, and the Tencent Hy Team that focuses on what researchers call embodied cognition, meaning a machine's ability to understand and reason about the physical world the way a robot might need to. The model combines language and vision so it can reason about images and video, imagine what will happen next after an action, and plan out steps toward a goal. The README describes three core abilities. The first is embodied understanding and reasoning, where the model can answer questions and explain its reasoning about images or short video clips, similar to how a person might describe what they see and predict what happens next. The second is world state prediction, where the model imagines and generates the frames that would follow if a particular action were taken in the physical world. The third is joint subgoal planning, where a complex task is broken into steps, and for each step the model produces both a description of the next action in words and an image of what the world should look like once that step is done. The project ships as Python code together with pretrained model weights hosted on Hugging Face, and includes example scripts for several tasks: generating an image from a text prompt, predicting several future frames from a single observed image, answering questions about an image, and running a full multi step planning demo on bundled example scenes. Running it requires Python 3.10 or newer and a CUDA capable GPU, since the model relies on flash attention for speed. The authors note that a benchmark called RxBrain-Bench and fine tuning code for some of the model's capabilities are still planned but not yet released, while the technical report, inference code, and model weights are already available. The project is released under the Apache License 2.0.