Progress in Humanoid Robot World Models
RemiCadene · x · 2026-07-17
A repost highlights that UMA is advancing latent world models for humanoid robots, accelerated by a SPRIND grant. The cited content traces a research trajectory: a long-term pursuit of scaling learning with minimal supervision and efficient data collection, including self-supervision, third-person imitation, and aligning different modalities/views/embodiments into a shared latent space.
The author notes that while few truly focus on the frontier of AI for robotics long-term, this specific line of research has already seen progress across multiple layers of the learning stack.
Related event: Remi Cadene Hires for Embodied World-Models Team(5 posts)→
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