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Achieve near-plaintext LLM inference speeds with strong privacy guarantees and minimal accuracy loss by jointly obfuscating data and model parameters – a first for models at the 671B scale.
Ditch discrete waypoints: VLA models can now generate smooth, physically plausible robot trajectories by directly regressing continuous action functions.
Event-based motion segmentation can now run 800x faster thanks to a clever normal flow representation and graph cut optimization.
