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HERO enables robots to autonomously evolve manipulation skills from scratch, drastically reducing reliance on human demonstrations.
Transforming diverse visual tasks into a unified RGB format enables a single model to excel across multiple domains without task-specific tuning.
Achieving 100% success on complex robotic tasks with just one demonstration could revolutionize how we approach real-world robotic learning.
Current AI models miss critical tumor detections in underrepresented demographics, revealing a hidden bias that could compromise patient outcomes.
