PhysProbe
Nebius.Build SFPhysProbe is a self-improving robot skill framework that uses predictive world models to make robots safer. 8 world models benchmarked on Nebius Token Factory for physics prediction — Qwen3-235B wins at 90% accuracy in 696ms, 3x faster than Claude, 33x faster than Grok. When models agree, the robot skips probing. When they disagree, one gentle 5N touch gives 94% certainty. When the robot fails, an AI swarm (Diagnostician → Inventor → Critic) invents new skills automatically. SkillsBench evaluation: +34pp skill delta across 750 trials, more than double the industry average. Success rate: 60% → 94%. Catastrophic failures: 34% → 8%. 73 builds. Solo project by Sidra Miconi.
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