Sudo, valued above $2 billion, unveils embodied model Sudo R1 with zero real-robot data and ~98% first-try grasp success

20亿美金苏度科技具身首秀即大招！0真机数据，zero-shot，跑出98%首次抓取成功率

Sudo unveiled embodied model Sudo R1 and says it achieved about 98% first-try grasp success in 200+ zero-shot tests with zero real-robot training data, nearing 100% within two attempts. The post says the 60-minute run covered 100+ unseen objects, including transparent, metallic, soft, and reflective items, using integrated world-model and reinforcement-learning training on a high-fidelity simulator. It also says Sudo is valued above $2 billion and is working with CATL, but the post does not disclose round size, benchmark protocol, or third-party validation.

Why it matters: Strong HKR-H/K/R: the zero-real-data, zero-shot, 98% claim is novel and concrete, and it hits robotics' data-cost nerve. Kept below 85 because the metrics are self-reported; funding amount, benchmark definition, and third-party validation are not disclosed.