Safeworld 融资1200万美元，用仿真验证生成式AI机器人安全性
原标题：Can Safeworld convince people that gen AI robots won’t hurt them?
AI 摘要
卡内基梅隆大学安全 AI 实验室主任丁昭博士与创业高管 Kyle Wong、机器学习工程师 Simo Rachidi 共同创立 Safeworld，旨在解决生成式 AI 驱动机器人的安全验证问题。该公司今日结束隐身模式，获得由 Shine Capital 和 a16z Speedrun 领投的超 1200 万美元种子轮融资。Safeworld 通过在 Genesis、MuJoCo 等仿真环境中构建真实人类模型，对机器人控制系统进行数千次场景测试，以评估其在非结构化环境中的安全性。公司已与 Gritt Robotics 合作，但产品形态（平台还是服务）仍在探索中。
正文节选
The big trend in robots is handing the keys over to a generative AI model, but that brings with it a problem: that architecture isn’t predictable the way traditional algorithms are. How can you be sure your brand new humanoid will be safe? Dr. Ding Zhao, who directs the Safe AI lab at Carnegie Melon University, has been working on this problem for almost his entire career. Now, along with veteran start-up executive Kyle Wong and machine learning engineer Simo Rachidi, he’s founded a company, Saf