科技公司迫切想要拍摄你做家务的画面。
内容总结：
美AI公司推免费家政服务：以清洁换录像，采集家庭数据训练家务机器人
本周，一家名为Shift的人工智能训练初创公司宣布，将为纽约居民提供免费家庭清洁服务。该公司还计划将业务扩展至伦敦等其他城市。这一模式背后的逻辑是，科技公司正迫切需要真实世界的数据来训练机器人完成日常家务。
然而，天下没有免费的午餐。作为交换，Shift要求拍摄清洁工在用户家中的工作过程：擦洗餐具、擦拭台面、除尘拖地等所有琐碎家务的录像。这些视频将成为训练家务机器人的关键素材——毕竟，教会机器人在物理世界中操作远比训练聊天机器人复杂得多。
与从互联网轻松抓取的文本、图片和视频不同，物理世界的数据难以大规模获取，更难以在不付费的情况下悄悄采集。这成为开发物理人工智能公司的巨大瓶颈。Shift等企业正通过创意方式破解难题，例如直接向用户付费换取家务录像。
事实上，这种用数据换取服务的形式并不新鲜。从会员卡到智能电视，企业长期以折扣和便利换取用户数据。但如今，数据采集的触角正伸向最私密的家庭空间。在印度，家政平台Pronto已有类似操作，尽管声称用户可自愿选择是否录制，仍引发市场争议。而硅谷的Human Archive公司甚至推出“摄像头帽”，让零工工人佩戴后从第一视角记录日常活动。
更值得关注的是，部分公司正在建立“数据农场”，让工人反复完成叠毛巾、取杯子等固定动作，通过传感器精确捕捉每个细节。即使市面上已有一些机器人产品，真正的全自动化仍遥不可及——许多企业依赖远程人工干预来补救机器人卡壳的窘境，这些数据同样被用于训练。
简而言之，人类亲手完成家务的录像，正成为训练替代人类做家务的机器人的“燃料”。目前，你可能需要让戴摄像帽的清洁工免费打扫房间；而未来，你将花钱购买那个用你的数据训练出来的机器人。
中文翻译：
本周，一家名为Shift的AI训练初创公司宣布，将免费为纽约居民打扫房屋。该公司还计划将业务扩展至伦敦等其他城市。环顾我的公寓，我立刻理解了这一做法的吸引力所在。
科技公司迫切希望拍摄你从事家务劳动的画面。初创公司正斥资购买训练机器人所需的真实世界数据。
但有个条件——总会有条件的。作为免费清洁的交换条件，Shift要求拍摄清洁人员的工作过程：擦洗餐具、擦拭台面、掸去桌尘、拖净地板。他们想要记录一切——那些我们恨不能外包的枯燥家务劳动的全部影像记录。这正是机器人公司竞相教会机器完成、以便向我们兜售替代方案的工作。
这比听上去困难得多。与近年来爆火的聊天机器人、图像生成器等AI工具不同，机器人必须应对物理世界。这意味着要理解空间、运动、力道、摩擦、千奇百怪的形状与材质、棘手的光线条件，以及人类及其他有机生命体往往凭本能就能掌握的一切。这也就是为什么那些对我们来说轻而易举的事情——比如叠衣服、拿起苹果、倒杯水——却让机器人专家在编程时抓狂不已。
教会机器完成这些事需要数据，而且是海量数据。文本、图像和视频可以轻松从互联网上大规模抓取——事实上它们也确实被这样抓取了，且常常未向创作者支付任何报酬。但物理世界的数据更难获取，想要悄无声息地免费获取则更是难上加难。这意味着获取高质量数据已成为开发物理AI的公司的巨大瓶颈。这是一块利润丰厚的蛋糕，因此像Shift这样的公司开始各显神通。
它们并非孤例。在印度，近期报道揭露家政服务平台Pronto一直将客户住所作为AI训练素材的来源，拍摄内容包括烹饪、清洁、洗衣等家务。Pronto声称只在客户明确同意的情况下才进行拍摄——不过客户除了获得一份影像副本外，似乎得不到其他回报——但这一做法仍在市场引发强烈反弹，竞争对手纷纷坚称从未在住宅内拍摄AI训练视频，也无意这么做。
其他初创公司则专注于扩大数据采集规模。例如，硅谷的Human Archive公司希望与Pronto这样的企业合作，让零工工人佩戴并不时尚的摄像帽录制日常活动。这些帽子从佩戴者视角采集影像，正是机器人公司教会机器理解人类如何在物理空间活动所需的"自我中心视角"或第一人称数据。与此同时，Shift也在直接面向消费者，据称已付费让15个国家数万人通过其应用记录日常活动。
还有一些公司完全绕开实用劳作。他们付费让工人反复执行完全相同的体力任务，同时用摄像机和传感器捕捉每个动作。这类精心布置的数据工厂旨在将机械的体力活动——叠毛巾、捡杯子、搬箱子——转化为价值足够高昂的AI训练素材，以证明雇人创造这些数据的合理性。
部分数据则来自已投入实际应用的机器人。尽管外界炒作不断，真正的自动化仍遥不可及——正因如此才需要海量数据——但企业仍热衷于推广产品。它们会利用客户家中的数据来改进产品。许多公司还依赖远程工作人员在机器人必然卡壳时介入操作，这些数据同样会被收录。
当然，用数据换取价值并非新鲜事。多年来，企业一直在以折扣、便利和免费服务换取用户数据的访问权限：从会员卡、网络追踪器，到行车记录仪、监控驾驶行为的保险应用，还有那台无休止播放广告的智能电视。
真正新鲜的是企业愿意付费购买的数据类型。就目前而言，这意味着或许可以让人戴着时髦帽子免费为你打扫房间，这样有朝一日，企业就能向你推销能代劳此事的机器人。
英文来源：
This week, an AI training startup called Shift said it would clean New Yorkers’ homes for free. It has plans to expand into other cities as well, including London, and looking around my flat, I get the appeal.
Tech companies desperately want to film you doing chores
Startups are paying people for the real-world data needed to train their robots.
Startups are paying people for the real-world data needed to train their robots.
But there’s a catch. There’s always a catch.
In exchange for the cleaning, Shift wants footage of its cleaners at work: scrubbing dishes, wiping counters, dusting tables, mopping floors. It wants everything. Video of all the boring domestic labor we’d happily outsource if we could — and that robotics companies are racing to teach machines to do so they can sell us something to do it for us.
That’s harder than it sounds. Unlike chatbots, image generators, and other AI tools that have exploded in recent years, robots have to deal with the physical world. That means understanding space, motion, force, friction, weird shapes and materials, awkward lighting, and everything else that humans — and other organics — tend to grasp instinctively. It’s why things that are generally easy for us, like folding clothes, picking up an apple, or pouring a glass of water, have proven so maddening for roboticists to codify.
Teaching machines to do those things takes data. Lots of it. Text, images, and videos could be easily scraped from the internet at an industrial scale. And they were, often without compensating the people who made them. The physical world is harder to scrape, and harder still to scrape quietly without paying for it. This means access to high-quality data is a massive bottleneck for companies developing physical AI. It’s a lucrative opportunity, so companies like Shift are getting creative.
They’re not alone. In India, recent reporting revealed that home services platform Pronto has been using clients’ homes as a source of AI training footage for chores like cooking, cleaning, and laundry. Pronto says it only records footage if customers explicitly opt in — it’s not clear what customers get in return, other than a copy of the footage — but the practice still set off a wave of backlash in the market, with rival startups insisting they have never recorded inside homes to train AI and have no plans to do so.
Other startups are focused on trying to scale data collection. Silicon Valley-based Human Archive, for example, hopes to partner with companies like Pronto and have gig workers record their activities using not-so-stylish camera caps. The hats collect footage from the wearer’s point of view, exactly the kind of “egocentric” or first-person data robotics companies need to teach machines how people navigate physical space. Shift, meanwhile, also taps consumers directly, and claims to have paid tens of thousands of people across 15 countries to record their activities through its app.
Some companies are skipping useful work altogether. Instead, workers are paid to complete the exact same physical tasks again and again while cameras and sensors can capture every movement. Such staged data farms are designed to turn rote physical activity — folding towels, picking up cups, carrying boxes — into AI training material valuable enough to justify paying people to create it.
And some data is generated by robots already out in the world. Despite the hype, true automation is still a long way away — hence the need for all this data — but companies are keen to ship products anyway. They’ll use data from customers’ homes to improve the product. Many companies rely on remote workers to step in when the robots inevitably get stuck. They’ll use that data too.
Of course, the act of trading data for something of value is not new. Companies have been offering discounts, convenience, and free services in exchange for access to your data for years, from loyalty cards and cookies to dashcams, insurance apps monitoring how people drive, and that heinous smart TV that’s always showing ads.
What’s new is the kind of data companies are willing to pay for. For now, that means maybe letting a human clean your home in a snazzy hat for free so that, eventually, a company can sell you a robot to do it instead.