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TurboVLA introduces a new Vision-Language-Action paradigm that directly maps vision and language to action, achieving 97.7% success on LIBERO with only 0.2B parameters and real-time inference at 32 Hz on consumer GPUs, significantly reducing computational cost.
Introduces two projects related to robot world models: Awesome-WAM (OpenMOSS) includes papers such as World Action Models and DreamDojo; awesome-physical-ai curates a collection of papers on VLA models, world models, and embodied foundation models (including NVIDIA Cosmos Predict2.5).
Google DeepMind introduces Gemini Robotics On-Device, an efficient VLA model optimized to run locally on robotic devices, enabling low-latency operation and offline capability while maintaining strong dexterous manipulation and task generalization. The model can be fine-tuned with as few as 50-100 demonstrations and comes with an SDK for developers.