Yacine renders 8,000 training worlds at 10M frames/sec on a single GPU
yacineMTB · x · 2026-09-28
YacineMTB details his embodied-AI training pipeline: with custom renderer optimizations, a single GPU renders 8,000 simulated worlds at roughly 10 million frames per second, and near-unlimited worlds can be kept ready to swap in per training episode. He calls it "domain randomization on steroids," noting 8k was simply the batch size that worked best in experiments — a striking example of extreme parallel-simulation optimization for robot policy training.
Related event: Ex-X AI dev claims single GPU renders 8,000 worlds at 10M fps(2 posts)→
More from Embodied
- Lightwheel AI and Dexmate's Vega robot set for IROS 2026 booth — jonstephens85 · 2026-09-28
- 'AI will never replace welders' — meanwhile, welding robots in South Korea — robleclerc · 2026-09-28
- Critic: Meta's VR glasses fall short on resolution and FOV — mallow610 · 2026-09-28
- Why 8,000 worlds? Yacine: just the batch size that worked best in experiments — yacineMTB · 2026-09-28
- Watch Opus design a 3D asset, print it, and have a robot arm retrieve it — burny_tech · 2026-09-28
- Robot spotted collecting embodied AI data at a night market — xiaosun86 · 2026-09-28