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Nature Will Debuts Natura-1, a 50B-Parameter Embodied Foundation Model Trained on One Million Hours of Human Experience
On October 13, Nature Will—founded by Ding Ning, assistant professor and doctoral supervisor at Tsinghua University's Department of Electronic Engineering—released Natura-1, its first general-purpose embodied foundation model, along with a technical report. The 50-billion-parameter mixture-of-experts model was pretrained on more than one million hours of first-person human video and can drive a 20-DOF dexterous hand within a 100-millisecond control loop.
UC Berkeley's SuperMimic Trains Humanoid Whole-Body Control on a Single GPU in 3 Hours, Surpassing 128-GPU Baseline
A UC Berkeley team introduced SuperMimic, a framework that uses a single differentiable world model to scale humanoid whole-body control. The approach trains on a single NVIDIA H100 GPU in 3 hours to outperform the SONIC baseline, which required 128 NVIDIA L40 GPUs over 7 days, reducing GPU-hour costs by more than 1,000 times.