LDA-1B and the Case for Never Throwing Robot Data Away
from Embodied AI 101 Hosted by Shaoqing Tan
Scales a latent dynamics action model to 1B parameters by ingesting diverse embodied datasets into a unified training pipeline for generalist robot policies. In this episode of Embodied AI 101, we explore "LDA-1B and the Case for Never Throwing Robot Data Away". We break down the research, methodology, and real-world implications for robotics, AI, and physical intelligence. Embodied AI 101 covers the latest research at the intersection of AI and physical intelligence — robotics, manipulation, world models, and the path from digital intelligence to embodied agents.
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What this episode covers
Scales a latent dynamics action model to 1B parameters by ingesting diverse embodied datasets into a unified training pipeline for generalist robot policies.
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