Beijing embodied-AI company Nature Will released Natura-1, a 50B-parameter MoE Transformer physical-world foundation model pretrained on roughly 1 million hours of first-person human experience data (about 61.7 million clips, 318,000 tasks, 14,000 scenes), then post-trained on limited robot data; it takes language and vision as input and drives 20-degree-of-freedom dexterous hands within a 100 ms control loop. The team says it combines dexterous manipulation with zero-shot instruction following, and published unedited one-take demos including wrapping wontons, making tea, packing parcels, applying a phone screen protector and writing calligraphy. On its own 12-dimension benchmark, Natura-1 scored 53.4 (Base) and 59.1 (Agentic) on the dexterous-hand platform, while π0.5 and OpenAI's GPT-6 Astra scored zero there (13.5 and 16.7 on a gripper platform); the team also reports action-prediction error dropping 47.7% on held-out human data and 67.7% on held-out robot data as training experience scaled from about 44,000 to 1 million hours.

Nature Will·Natura-1·Tsinghua University·+5