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slowly, or act quickly but lack robust planning. Frontier models typically depend on heavy compute, cloud inference or controlled settings, limiting real-world use under compute, latency and energy
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-language-action models, imitation and reinforcement learning, world models, multimodal perception, model compression and edge inference. A key aim is enabling robots to improve beyond initial demonstrations
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