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在宿迁，居民可以戴上JoyEgoCam，在叠被子、擦桌子、择菜等家务中记录动作；京东与宿迁联合建设的具身智能数据采集社区已于今年5月运行。与此同时，觅蜂科技旗下“觅蜂派”App已经上线，待正式向公众开放后，用户可以租用采集设备、领取任务，上传经审核有效的视频和数据后获得现金收益。
In Suqian, residents can wear JoyEgoCam to record their movements while folding blankets, wiping tables and preparing vegetables; the embodied-intelligence data-collection community jointly built by JD.com and Suqian began operating in May this year. Meanwhile, “Mifeng Pai,” an app owned by Mifeng Technology, has already launched. Once it formally opens to the public, users will be able to rent collection equipment, claim tasks, and receive cash payments after uploading videos and data that pass review.
规模是这条路必须回答的问题。姚卯青在8月31日的群访中，把具身智能下一阶段的数据需求指向“千万乃至亿小时”，并承认依靠现有模式线性复制“非常难”。传统数采工厂把机器人、遥操作设备、操作人员和模拟环境集中在一起，反复完成抓取、搬运、整理等任务；如果需求突然扩大，就不能只靠同步增加厂房、机器人和遥操作员。
Scale is the question this approach must answer. In a group interview on August 31, Yao Maoqing said that embodied intelligence’s data needs in the next phase could reach “tens or even hundreds of millions of hours,” acknowledging that it would be “extremely difficult” to replicate the existing model linearly. Traditional data-collection factories bring robots, teleoperation equipment, operators and simulated environments together to repeatedly perform tasks such as grasping, carrying and sorting. If demand suddenly expands, companies cannot rely solely on adding factories, robots and teleoperators at the same pace.
美国Figure正在验证另一种组织方式。其人形机器人数据项目Index此前已秘密运行4个月，普通人可以在家庭或工作场所完成做饭、清洁、洗衣、整理货架等任务并上传数据。截至8月25日，Index已覆盖108个国家，有超过4.4万名周活跃参与者上传1600多万条视频，Figure已向数据贡献者支付1500万美元，并计划未来12个月在数据和算力上投入超过10亿美元。
Figure in the United States is testing another organizational model. Its humanoid-robot data project, Index, had previously operated in secret for four months. Ordinary people can perform tasks such as cooking, cleaning, doing laundry and arranging shelves at home or in the workplace, then upload the data. As of August 25, Index had covered 108 countries, with more than 44,000 weekly active participants uploading over 16 million videos. Figure has paid data contributors $15 million and plans to invest more than $1 billion in data and computing over the next 12 months.
中国的做法正在分出几条路径：觅蜂更接近平台化众包，京东更接近企业场景加社区动员，贵州惠水则加入政府和地方资源协调。京东规划仅在宿迁发动超过10万名市民，覆盖家庭、办公室、工厂、物流、商店、环卫等100多个细分场景；更大的目标是发动内部超过10万名员工和外部50万名各行业人员，在两年内积累超过1000万小时真实场景数据。当地披露，现有采集已覆盖8大产业门类、50余个真实场景，年交付上万小时高质量数据。
China’s approach is splitting into several paths: Mifeng is closer to platform-based crowdsourcing, JD.com is more focused on combining enterprise settings with community mobilization, while Huishui in Guizhou has added coordination by local government and regional resources. JD.com plans to mobilize more than 100,000 residents in Suqian alone, covering more than 100 specific settings across homes, offices, factories, logistics, stores and sanitation. Its broader goal is to mobilize more than 100,000 internal employees and 500,000 people from various industries externally, accumulating more than 10 million hours of real-world data within two years. Local authorities have disclosed that existing collection efforts cover eight major industries and more than 50 real-world settings, delivering more than 10,000 hours of high-quality data annually.
具体到普通人，眼前得到的是按审核通过的数据领取现金，而不是一套稳定的工资体系。行业中出现过“时薪15元”或“一天120元”的项目报价，但姚卯青强调，不同场景尚无标准定价，稀缺程度、进入难度和交付时效都会改变价格。对企业而言，拆散工厂的价值在于把设备带入真实工作和生活，而不是简单增加采集员；这可能让社会本身成为更大的数据生产场所。
For ordinary people, what is currently on offer is cash paid for data that passes review, rather than a stable wage system. Projects in the industry have offered rates such as “15 yuan an hour” or “120 yuan a day,” but Yao Maoqing stressed that there is no standard pricing across different settings. Scarcity, difficulty of access and delivery deadlines can all change the price. For companies, the value of dismantling the factory model lies in bringing equipment into real work and daily life, rather than simply adding more data collectors; society itself could become a much larger data-production site.
真正的门槛随之从招人转向获得现实世界的进入权。家庭涉及隐私，企业涉及商业机密，医院、工厂、仓库和养老机构还牵涉第三方权益；会修车的工人，也不代表可以戴着设备进入车间并把全过程上传。在以个人同意作为个人信息处理基础的情况下，中国的个人信息保护法要求取得个人在充分知情下自愿、明确作出的同意；数据安全法要求数据收集采取合法、正当方式。技能属于工人、场景属于企业、设备由数据公司提供、平台负责加工、机器人公司买走数据的链条，仍需要回答谁拥有数据以及贡献动作的人如何分享价值。因而，“给机器人打工”更像一种正在形成的生产方式，而不是成熟职业。
The real barrier is therefore shifting from recruiting people to securing access to the physical world. Homes involve privacy, while companies involve commercial secrets; hospitals, factories, warehouses and elderly-care institutions also raise questions about the rights of third parties. A mechanic’s ability to repair cars does not mean the worker can wear a device into a workshop and upload the entire process. Where individual consent serves as the basis for processing personal information, China’s Personal Information Protection Law requires voluntary and explicit consent given with full knowledge of the circumstances; the Data Security Law requires data collection to use lawful and proper methods. The chain in which skills belong to workers, settings belong to companies, equipment is supplied by data firms, platforms process the data and robot companies buy it still has to answer who owns the data and how the people contributing the movements should share in its value. “Working for robots” is therefore better understood as a production model still taking shape than as an established profession.