Groundbreaking AI Model Learns from Physical World Interactions
Summary
A pioneering artificial intelligence model, trained on real-world physical interactions, learns to adapt and generalize through a feedback loop between its virtual embodiment and the environment, with open-source WALL models enabling further research and applications.
Key Points
- Building embodied foundation model to capture physical interaction data
- Enabling emergence of generalizable intelligence through model-body feedback loop
- Providing training and inference code for WALL series open-source models