We unpack DeepMind's Gemini ER 1.6, an embodied reasoning model that grounds language in physical space with precise pointing, multi-camera success checks, and agentic action. See how its 'frontal lobe' plans tools and tasks, writes on-the-fly code to measure dial angles, and coordinates with 'VLA' muscle models to safely operate in messy environments—from reading gauges to Spot inspections. We'll explore the architecture, grounding techniques, safety constraints, and what this means for the future of autonomous robots and AI training.

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