Safeworld公司今日宣布从隐身模式推出，致力于解决生成式AI机器人的安全问题1。该公司由卡内基梅隆大学Safe AI实验室主任丁昭、创业老将Kyle Wong和机器学习工程师Simo Rachidi联合创办，已募集超1200万美元种子资金，由Shine Capital和a16z Speedrun领投，Box Group、卡内基梅隆大学捐赠基金、Innovation Endeavors和SV Angel参投1。
Safeworld的核心技术是在仿真环境中利用真实人类模型对机器人控制系统进行评估，以验证AI机器人在复杂、非结构化环境中与人类工作者交互的安全性1。a16z Speedrun合伙人Jonathan Lai指出，"现在正是制定行业安全标准的时机，趁机器人还在设计和部署阶段。等到机器人在家庭中与孩子发生碰撞导致安全事故，那就太晚了"1。创始人丁昭表示，"我们可能会成为这个领域第一家盈利的公司，因为任何想要部署的人都需要付钱让我们处理这个问题"1。
Safeworld, a newly launched startup focused on ensuring the safety of generative AI robots, has announced its public debut alongside a seed funding round exceeding $12 million.1 The company was founded by Zhao Ding, director of Carnegie Mellon University's Safe AI Lab, alongside venture veteran Kyle Wong and machine learning engineer Simo Rachidi.1 The funding round was led by Shine Capital and a16z Speedrun, with participation from Box Group, Carnegie Mellon University's endowment fund, Innovation Endeavors, and SV Angel.1
Safeworld's core approach involves evaluating robot control systems by testing them against real human models in simulated environments, aiming to verify the safety of AI robots operating alongside human workers in complex, unstructured settings.1 According to Jonathan Lai, a partner at a16z Speedrun, the timing is critical for establishing industry safety standards while robots are still in the design and deployment phases.1 "Now is the moment to set industry safety standards while robots are being designed and deployed. If we wait until robots collide with children in homes, it will be too late," Lai stated.1
Ding expressed confidence about Safeworld's market positioning, suggesting the company could become the first profitable player in this emerging field.1 "We will likely be the first profitable company in this space, because anyone who wants to deploy robots will need to pay us to handle this," Ding said.1
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