PrimeBot's PrimeSim: a generalist world model simulator trained on cross-embodiment demos
Travis Davies · hf · 2026-11-04
PrimeBot Research, with Southeast University, SJTU, PKU and others, released PrimeSim, an action-conditioned multiview world model simulator trained on 200k+ hours of cross-embodiment robot demonstrations. A robot world model serving as a simulator must faithfully follow commanded actions, stay consistent across camera views, and sustain coherent long-horizon rollouts. PrimeSim addresses these via progressive midtraining, unified action representations, view-aware attention, and hierarchical memory, enabling consistent long-horizon robot simulation and policy optimization.
More from Embodied
- 22 Creative SAM 3.1 Use Cases From Meta's AI Developer Hackathon, From Wildfire Detection to Document Reassembly — Vjeux · 2026-11-04
- Ex-OpenAI robotics intern breaks down viral Astra robot-painting demo on Cerebras podcast — AccBalanced · 2026-11-04
- Embodied Agent Arena: Closed-Weight VLMs Lead All Five Robot Task Domains, Open-Weight Models Lag — Haojian Huang · 2026-11-04
- Physical AI Hackathon in SF Nov 7–8 features Dream-1 world action model and robot arms — Scobleizer · 2026-11-04
- Figure robot office demo looks like a sci-fi movie, says CEO Brett Adcock — adcock_brett · 2026-11-04
- 'Beyond Validation Loss': best pretraining checkpoint may hurt downstream RL fine-tuning — SongShuran · 2026-11-04