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The data pyramid framework reveals how the interplay of diverse data sources can unlock new capabilities in embodied agents, highlighting critical gaps in current methodologies.
MLLMs stumble badly when asked to reason about safety in lab settings, dropping 32% in performance compared to general knowledge, revealing a critical gap for real-world deployment.
