Kicking Robots, by James Vincent
James Vincent is a writer living in London. This article was supported by a grant from the Tarbell Center for AI Journalism. 詹姆斯·文森特是一名居住在伦敦的作家。本文得到塔贝尔人工智能新闻中心的资助。
🛠️ 科技/技术 (Tech) | 信息密度：高 | 🆕 新颖度：中
🎯 核心信号 (The Signal)
• 一句话结论：人形机器人产业充斥炒作与表演，尽管AI取得进展和资本蜂拥而至，现实中的技术远未达到”自主通用劳动力”的承诺——目前只有3家美国公司有试点项目，且单台机器人往往只能在特定场景完成单一任务。
• 关键证据/要点： ▪ 部署现状极其有限：Figure AI宣称有”机器人舰队”，实际BMW工厂仅有1台在运作；Apptronik与梅赛德斯只是”探索潜在用途”；即便务实的Agility也仅与GXO Logistics试用2台机器 ▪ 泛化能力缺陷：机器人在特定任务上表现可以（如切水果、倒水），但无法识别”何时需要做这件事”或在环境变化时自适应；Boston Dynamics副总裁坦言”不能保证完美精准度或可靠性” ▪ 演示造假现象普遍：1X的NEO咖啡演示中，机器人仅倒水，人类员工完成剩余步骤却被标榜为”NEO做的”；多数惊人特技（侧手翻、杂技）都是一次性演出，缺乏真实工作能力 ▪ 中国虽产量大但质量参差：每月可生产数千台，但Robert Stokes称20%的Unitree机器人出厂即损坏，需修理后才能使用
🛡️ 批判性视角 (Critical Check) • 逻辑漏洞/风险点： ▪ AI类比陷阱：作者与受访者频繁用ChatGPT的成功类比人形机器人前景，但两者本质不同——语言模型只需生成文本，机器人需在物理世界精准执行，容错成本远高 ▪ 演示vs现实的鸿沟：业界热衷展示单点能力（做俯卧撑、跳舞），但这些都是受控环境下的表演；真实场景如”给婴儿倒茶”涉及的感知-决策-执行链条复杂得多，目前无解 ▪ 地缘政治焦虑放大预期：Chowdhury坦言”中国会打印自己的劳动力”这种末世论式恐惧正推高融资热度，但技术成熟度与战略焦虑脱钩——这是帕斯卡赌注式的心理：因为后果太极端就被迫认真对待不太可能发生的事 ▪ 供应链忽视：分析仅关注硬件和AI，忽视了真实部署需要的标准化、安全认证、法律框架——ASTM仍在讨论基础标准问题
• 立场与意图： 深度新闻调查：作者亲赴德州、旧金山实地采访，与1X被拒访问形成对比，揭示了行业的信息不对称（选择性公开+媒体筛选） 冷峻的技术现实主义：最终落点是慎重乐观——技术会进步，但速度远慢于预期，且每一步都充满复杂性（如”洗碗机问题”的类比）
▪ 非营销软广，而是对炒作与现实落差的精准解剖
🌲 关键实体与作用 (Entities & Roles)
• Elon Musk：产业的最大话题制造者与期货承诺者。2021年AI Day上用舞蹈演员替代Optimus原型，完美诠释了”用壮观掩盖技术不足”；他的存在本身就加速了整个行业的融资与媒体关注，尽管他的时间表从不兑现 • Apptronik (Jeff Cardenas)：务实与乌托邦并存的代表。建造Apollo原型机是业界最成熟的演示之一，但Cardenas的言辞滑向”四百亿年人类体验”这类夸张承诺——典型的硅谷式未来论叙事 • Boston Dynamics：业界良心。拥有最成熟的技术与数据训练体系，却诚实地说”家用机器人未来可预见不太可能”；其VP的警告（“机器人只能用这台咖啡机做这杯咖啡”）堪称全文最清醒的声音 • 1X Technologies (Børnich)：高风险承诺者。拒绝媒体采访而只与YouTube频主合作，宣称2028年能年产百万台NEO，但原型仍在内部测试——信息不透明度最高 • ChatGPT/OpenAI：无形推手。虽未被直接提及，但其”大数据→突发能力”的范式被全行业借用，导致对vision-language-action模型（VLA）的过度预期 • 中国制造商（Unitree等）：数量游戏的玩家。受益于规模经济与供应链完整性，但质量控制与软件成熟度落后美国一代；代表了”安卓vs苹果”的产业分化趋势
💡 启发性思考 (Heuristic Questions)
- 如果一台机器人在实验室能100次中99次成功夹取脆弱物品，为什么我们仍不信任它在真实家庭中处理我们的瓷器或婴儿？——这揭示的是”单点能力≠系统可靠性”的根本差异，也许才是真正的技术瓶颈所在：不是做某件事，而是知道何时该做，以及在失败时自我纠正。
You can learn a surprising amount by kicking things. It’s an epistemological method you often see deployed by small children, who target furniture, pets, and their peers in the hope of answering important questions about the world. Questions like “How solid is this thing?” and “Can I knock it over?” and “If I kick it, will it kick me back?”
通过踢东西你可以学到意想不到的许多东西。这是一种认识论方法，你常在小孩子身上看到，他们会踢家具、宠物和同伴，试图回答关于世界的重要问题。比如“这东西有多坚固？”、“我能把它踢倒吗？”以及“如果我踢它，它会反踢我吗？”
Kicking robots is something of a pastime among roboticists. Although the activity generates anxiety for lay observers prone to worry ing about the prospect of future retribution, it also happens to be an efficient method of testing a machine’s bal ance. In recent years, as robots have become increasingly sophisticated, their makers have gone from kicking them to shoving them, tripping them, and even hitting them with folding chairs. It may seem gratuitous, but as with Dr. Johnson’s infamous response to Bishop Berkeley’s doctrine of immaterialism, there’s something grounding about applying the boot. It helps separate what’s real from what’s not.
在机器人学界，踢机器人几乎是一种消遣。虽然这种行为会让那些担心未来报复可能性的外行观察者感到焦虑，但它也是一种有效测试机器平衡性的方式。近年来，随着机器人越来越复杂，它们的制造者已经从踢它们发展到推搡、绊倒，甚至用折叠椅击打它们。看起来或许多此一举，但就像约翰逊博士对伯克利主教无形主义学说那臭名昭著的回答一样，动脚一踢有其落地感。这有助于分清什么是真实的，什么不是真实的。
All of this is going through my head in April, when I find myself face-to-face with a robot named Apollo. Apollo is a humanoid: a robot with two arms and two legs, standing five feet eight inches tall, with exposed wires, whirring motors, and a smooth plastic head resembling a mannequin’s. Like so many humanoids, Apollo exemplifies the uncanny, hyperreal nature of modern robotics, simultaneously an image from science fiction and a real, tangible machine.
所有这些念头在我四月时涌上心头，那时我与一台名为阿波罗的机器人面对面。阿波罗是个类人机器人：有两只胳膊两条腿，身高五英尺八英寸，露出电线、嗡嗡作响的马达，光滑的塑料头看起来像个人体模型的头。像许多类人机器人一样，阿波罗体现了现代机器人学那种令人毛骨悚然的超真实特性，既像科幻作品中的意象，又是一个真实、可触的机械体。
Robots like Apollo are seemingly everywhere these days. There are headlines about Chinese bots running half mara thons, ominous videos of muscled hu manoids twitching on gantries, clips of robot fight clubs. Sometimes you get the feeling that these machines constitute a fifth column of sorts— a not-so-secret cell, growing in number, biding its time, preparing for the uprising. Econo mists are looking forward to it. Around the world, they point out, population growth is slowing and labor shortages are spreading. Without humanoids to step into the breach, and quickly, the global economy could descend into chaos. Bank of America forecasts that there will be at least a million humanoid robots shipped annually by 2035, while Morgan Stanley predicts that more than a billion will be in use by 2050. If all goes according to plan, robotics could constitute the largest industry in the world, generating annual revenue up wards of $5 trillion. Elon Musk, that sage of understatement, claims that Tesla’s own Optimus robot will one day “be more productive than the entire global economy.”
像阿波罗这样的机器人如今似乎无处不在。关于中国机器人跑半程马拉松的头条、肌肉型人形机器人在龙门架上抽搐的令人不安的视频、机器人大乱斗的片段层出不穷。有时你会觉得这些机器构成了一种第五纵队——一个不那么秘密的细胞，数量在增长，等待时机，筹备起义。经济学家对此甚为期待。全球范围内，他们指出，人口增长正在放缓，劳动力短缺正在蔓延。如果没有人形机器人迅速填补这一空缺，全球经济可能会陷入混乱。美国银行预测，到 2035 年每年将至少出货一百万台人形机器人，而摩根士丹利则预测到 2050 年将有超过十亿台在使用中。如果一切按计划进行，机器人产业可能成为世界上最大的行业，年收入超过 5 万亿美元。那位低调的睿智者埃隆·马斯克声称，特斯拉自己的 Optimus 机器人有一天“将比整个全球经济更有生产力”。
Apollo, October 2025
Apollo’s creator, the U.S. startup Apptronik, is a frontrunner in this emerging industry. The company says it’s building the first general-purpose commercial robot, a machine that will one day be able to take on any type of physical labor currently performed by humans, whether cleaning houses or assembling cars. Not knowing what to believe from what I’ve seen on social media, I’ve trav eled from London to Austin, Texas, to see Apollo for myself. Against prophecies of doom and salvation, “stability testing” seems like a crude way to gauge the technology’s development, but it’s a good place to start.
阿波罗的制造者是美国初创公司 Apptronik，该公司在这一新兴产业中处于领先地位。公司称正在打造首款通用商业机器人，这种机器未来能够承担任何目前由人类执行的体力劳动，无论是打扫房屋还是组装汽车。因为不确定社交媒体上看到的内容是否可信，我从伦敦来到得克萨斯州奥斯汀亲眼见证阿波罗。与末日或救世的预言相比，“稳定性测试”似乎是评估这项技术进展的一个粗糙方式，但这是一个不错的起点。
As I square up to Apollo in a plexiglass arena, my first instinct is, naturally, to raise a foot. But the kick test is too dangerous for visiting journalists, I’m told. Instead, someone hands me a wooden pole with a piece of foam taped around one end and mimes pok ing the machine in its chest. Ah, I think, the scientific method. In front of me, as various motors rev up to speed, the robot shuffles in place, looking like an arthritic boxer readying for a fight. On the other side of the plexiglass, a group of engineers chat casually with one another and glance over at a bank of monitors. One of them gives me a thumbs-up. Have at it.
当我在有机玻璃围成的竞技场里正面对着阿波罗时，我的第一反应当然是抬起脚。但有人告诉我，踢测试对来访的记者来说太危险了。于是，有人递给我一根木杆，杆的一端缠着一块泡沫，示意我用它戳机器的胸口。啊，我想，这是科学方法。我的面前，各种电机开始加速运行，机器人在原地挪动，看起来像个关节炎拳击手在做战前准备。在有机玻璃的另一侧，一群工程师若无其事地交谈着，偶尔瞥向一排监视器。其中一人向我竖起大拇指。来吧，试试。
My first shove is hesitant. I’ve been told that the prototype in front of me is worth around $250,000, and while breaking it would make for a good story, it would also be the end of my visit to Apptronik. In response to my prod, the bot merely teeters. It’s heavier than I’d expected, around 160 pounds. It feels, well, like a person. “Oh, you can do it harder than that,” says an engineer, and I jab forward again. Nothing. Apollo is still trotting on the spot. Fine, I think, I’ll give it a real push. Drawing back, I grip my makeshift spear and strike the robot hard in the chest. It staggers backward, stamping its feet, flinging its arms toward me in an appealingly human gesture. I’m struck by a flash of involuntary alarm, whether out of sympathy for a fellow being or fear of an expensive accident I can’t say. For a moment, the robot looks like it might fall, then regains its balance and returns to its position in front of me. I look at its blank face with wonder and disquiet. It seems pretty real to me.
我的第一次推搡有些犹豫。我被告知眼前的这个原型机价值约 25 万美元，虽然把它弄坏会是一个好故事，但也将意味着我在 Apptronik 的访问结束。回应我的推动，机器人只是摇摇晃晃。它比我预想的要重，大约 160 磅。感觉，嗯，像个人。“哦，你可以更用力一点，”一位工程师说，我又猛地向前刺去。没反应。阿波罗仍在原地小跑。好吧，我想，我就用真力气推一把。后撤，握紧手里的临时长矛，我重重地击中了机器人的胸口。它踉跄后退，跺着脚，向我甩出胳膊，做出一种颇有人情味的姿态。一阵不由自主的惊恐掠过我，是出于对同类的同情还是对一场昂贵事故的恐惧，我说不清楚。片刻间，机器人看起来似乎要倒下，随后又稳住了身子，回到我面前的位置。我带着惊奇和不安看着它那张呆滞的脸。对我来说，它看起来相当真实。
T he current era of humanoid hype has a clear inaugu ration date. On August 19, 2021, at Tesla’s AI Day, a press jamboree to promote the company’s latest tech and future plans, Musk took the stage and announced that he was building a robot. The machine—then known as the Tesla Bot, now called Optimus—would have “human-level hands,” he promised. It would be able to perform “dangerous, repetitive, boring tasks” and follow simple commands like “Go to a store and get me the following groceries.” Lacking a prototype to show the audience, Musk had arranged for a man in a spandex robot costume to stand in for the Tesla Bot. The figure mounted the stairs with cartoonishly stiff movements before breaking into a frenetic, seemingly improvised dance as dubstep blared from nearby speakers. After the dancer exited to scattered applause, Musk shuffled back onstage. “Obviously that was not real,” he said.
类人机器人热潮的当前时代有一个明确的开端日期。2021 年 8 月 19 日，在特斯拉的 AI 日——一次为宣传公司最新技术和未来计划而举办的媒体盛会——马斯克登台宣布他正在制造一台机器人。他当时称之为特斯拉机器人（现名 Optimus），承诺这台机器将拥有“类人的手”。它将能够执行“危险、重复、枯燥的任务”，并遵从诸如“去商店给我买以下这些杂货”之类的简单指令。由于没有原型向观众展示，马斯克安排了一名穿紧身洛卡棉机器人服装的人代替特斯拉机器人。那个人以夸张僵硬的动作上了台阶，随后在附近扬声器播放的颓废电音中爆发出疯狂、看似即兴的舞蹈。当舞者在零星的掌声中退场后，马斯克又蹒跚着回到台上。“显然那不是真实的，”他说。
Musk’s showcase captured perfectly the power of spectacle to mask technological shortcomings and bridge the gap between ex pectation and reality. But for those who’d been toiling away on humanoid robots for decades, Musk’s announcement was something more than a publicity stunt. “After Tesla Bot, the whole world sort of woke up to humanoids,” Jeff Cardenas, Apptronik’s co-founder and CEO, told me. The number of people working on the technology prior to Tesla’s AI Day pronouncement “could fit in a small room,” but Musk transformed the industry almost overnight, even if all the public had seen of the Tesla Bot was a slide deck and a gyrating man in a robot costume.
马斯克的展示完美地体现了壮观场面掩盖技术不足、弥合期望与现实差距的力量。但对于那些几十年来一直致力于人形机器人研发的人来说，马斯克的宣布不仅仅是一次公关噱头。“在特斯拉机器人大模型之后，全世界似乎都醒悟过来，开始关注人形机器人，”Apptronik 的联合创始人兼首席执行官杰夫·卡德纳斯告诉我。在特斯拉 AI 日宣布之前，从事这项技术的人数“还能挤进一个小房间”，但马斯克几乎在一夜之间改变了整个行业，即便公众所见的特斯拉机器人仅仅是一套幻灯片和一个穿着机器人服装摇摆的人。
After my bout with Apollo, Carde nas and I headed to Apptronik’s conference room. Cardenas is tall and handsome, one of those men who manages to straddle the jock-nerd divide, and whose behavior can be read as either supremely confident or socially oblivious. When he holds my gaze—which seems like all the time—I can’t decide whether he’s trying to intimidate me or win me over. I get the feeling it’s a bit of both.
在我和阿波罗的一番交手后，卡德纳斯和我前往了 Apptronik 的会议室。卡德纳斯高大英俊，是那种介于运动男与书呆子之间的人，他的行为既可以被解读为极度自信，也可以被看作社交迟钝。每当他与我对视——似乎是一直在对视——我无法判断他是在试图恐吓我还是在想赢得我的好感。我觉得两者都有一点。
In my decade of reporting on tech, the posture of executives has shifted from one of assumed friendliness to one of wariness and even antagonism. This is in part a result of tech’s embrace of alpha-male culture, but it’s also a defensive response to public disappointment with and mockery of the industry’s achievements (crypto, the blockchain, NFTs, etc.). I’m curious to see how Cardenas will try to sell me on humanoids—a risky technology that could be genuinely transformational, but that relies heavily on hype to rally interest and investors.
在我十年的科技报道生涯中，高管们的姿态已经从本来假定的友好转变为戒备甚至敌意。这部分是科技界拥抱“阿尔法男性”文化的结果，但也是对公众对行业成就（加密货币、区块链、NFT 等）失望并嘲讽的防御性回应。我很想看看卡德纳斯将如何向我推销类人机器人——这是一项可能真正具有变革性的高风险技术，但它在很大程度上依赖炒作来吸引关注和投资者。
To get a better idea of where Cardenas stands, I ask him what he thinks of Musk. He admits that the Tesla CEO doesn’t necessarily have “a consistent track record on timelines” (at the time of writing, reports suggest Tesla has slashed its production targets from five thousand to two thousand units for this year) but says that Musk has an instinct for knowing when technologies and markets align, proving himself with electric vehicles, reusable rockets, and satellite internet. “I thought Elon was a really good person to be an initial major evangelist,” Cardenas tells me. “If he was jumping into humanoids, certainly there had to be some reason why.”
为了更清楚地了解卡德纳斯的立场，我问他对马斯克的看法。他承认特斯拉 CEO 在时间表方面“并不一定一贯可靠”（撰写本文时，有报道显示特斯拉已将今年的产量目标从五千辆削减到两千辆），但他说马斯克有一种本能，能判断出技术和市场何时契合，他在电动汽车、可重复使用火箭和卫星互联网方面证明了自己。“我认为埃隆是一个非常适合成为最初主要传道者的人，”卡德纳斯对我说。“如果他要进入人形机器人领域，肯定是有原因的。”
And there was, indeed, a very clear reason: artificial intelligence. Engineers will tell you that there are a number of material factors underpinning the current boom in humanoids. Electric motors have become cheaper and more powerful; digital sensors are faster and more reliable; and there have been downstream benefits to battery performance thanks to investment in electric cars and drones. But the single most important factor—the one at the nexus of hype and potential—is the growth of AI and, in particular, the promise of deep learning. It’s this technology—the use of algorithms to mine vast stores of data for patterns—that has powered the development of large language models like ChatGPT, and that roboticists hope will push their own machines into the next stage of development.
而且确实有一个非常明确的原因：人工智能。工程师会告诉你，支撑当前类人机器人热潮的有多种实质性因素。电动马达变得更便宜、更强大；数字传感器更快、更可靠；由于对电动汽车和无人机的投资，电池性能也获得了下游收益。但最重要的单一因素——位于炒作与潜力交汇处的那个——是人工智能的增长，尤其是深度学习的前景。正是这项技术——利用算法在海量数据中挖掘模式——推动了像 ChatGPT 这样的大型语言模型的发展，机器人学家也希望它能把他们的机器推进到下一个发展阶段。
Instead of decoding the rules of human language from piles of text, these engineers are trying to emulate human dexterity by analyzing stores of video and sensor data. This training data is either generated by humans who control robots like puppets (a practice known as “teleoperation,” or “teleop”) or taken from virtual training environments, where tasks can be attempted using robot models over and over, at accelerating rates. The resulting systems go by a few different names but are most commonly known as vision-language-action models (VLAs) or large behavior models (LBMs). The hope is that they will provide brains for what are already pretty capable bodies.
这些工程师不是从大量文本中解码人类语言的规则，而是通过分析大量视频和传感器数据来模仿人类的灵巧。这些训练数据要么由像木偶一样控制机器人的人类产生（这种做法称为“远程操控”或“teleop”），要么来自虚拟训练环境，在那里可以使用机器人模型反复尝试任务，并以加速的速度进行。由此产生的系统有几种不同的称呼，但最常见的是视觉-语言-动作模型（VLA）或大型行为模型（LBM）。人们希望它们能为那些已经相当能干的机器身体提供“脑”。
The early fruits of this approach are just beginning to appear. In June, Figure AI, a humanoid-robotics startup, released a sixty- minute video of its prototype humanoid nimbly sorting variously sized parcels, the kind of work that’s easy for humans but challenging for machines. Figure AI’s CEO, Brett Adcock, told Bloomberg that the robot’s operations were running on a single AI neural network. “It’s taking camera frames in; it’s outputting the actions,” he said. This is a major change from robot control systems that resemble a set of step-by-step instructions: Go to X position and close grabber. Move to Y position and re lease grabber. Instead, Adcock and his peers are creating systems that gener alize rules from data, just like chat bots do. Thanks to demos like Figure AI’s, advocates claim that robotics is headed toward its own “ChatGPT moment,” a technical breakthrough that attracts investment and accelerates adoption. For others in the industry, though, the very phrase is anathema. It suggests that hype is clouding reality and that a bubble of rising stock prices and funding rounds is about to burst, setting back public confidence in robotics for years.
这种方法的早期成果才刚刚开始显现。今年六月，类人机器人初创公司 Figure AI 发布了一段六十分钟的视频，展示其原型类人机器人灵巧地分拣各种尺寸的包裹——这类工作对人类并不难，但对机器而言颇具挑战。Figure AI 的首席执行官 Brett Adcock 在接受彭博社采访时表示，机器人的操作由单一的 AI 神经网络驱动。“它接收摄像机画面作为输入；然后输出动作，”他说。这与那些类似逐步指令的机器人控制系统有重大不同：前往 X 位置并关闭抓手；移动到 Y 位置并释放抓手。相反，Adcock 和他的同行们正创建能够从数据中概括规则的系统，就像聊天机器人一样。借助像 Figure AI 这样的演示，支持者宣称机器人技术正走向其自身的“ChatGPT 时刻”——一项吸引投资并加速采纳的技术突破。然而对该行业的其他人来说，这个短语本身令人反感。它暗示着炒作正在模糊现实，股价和融资轮次攀升的泡沫即将破裂，从而在未来数年内削弱公众对机器人技术的信心。
In other words: Are humanoids more like Facebook, which was once so committed to virtual reality that it rebranded itself as Meta, a pivot that failed utterly after the company’s augmented- and virtual-reality division lost more than $45 billion in a matter of years? Or are they more like self-driving cars, which were a similarly flashy locus for investment and criticism but now seem to be transforming into viable businesses? It took Waymo, a subsidiary of Alphabet, about six years for its cars to rack up their first million miles of autonomous driving, but as of this summer its fleet drives two million miles every week.
换句话说：类人机器人更像曾经如此致力于虚拟现实以至于改名为 Meta 的 Facebook——这个转向最终彻底失败，该公司增强现实和虚拟现实部门在几年内亏损超过 450 亿美元？还是更像自动驾驶汽车，曾同样是吸引大量投资和批评的炫目焦点，但现在似乎正在转变为可行的业务？Alphabet 旗下的 Waymo 用了大约六年时间才让其汽车累计达到首个一百万英里自动驾驶里程，但截至今年夏天，其车队每周行驶两百万英里的自动驾驶里程。
In my conversation with Cardenas, we discussed the different ways robots already work alongside us. When I was catching my flight to Texas, for instance, I watched a floor-cleaning machine the size of a garbage bin sweep through Heathrow Airport. An older couple stopped and pointed as it trundled past, but most travelers ignored it. Then, after landing in Austin, I walked past a “robot barista” making coffee. The operation was pure spectacle: the robot was just a mechanical arm that held a cup underneath the nozzle of a machine. Here, I thought, are the two strands of robotics: one useful and invisible, the other theatrical and redundant.
在我与卡德纳斯的谈话中，我们讨论了机器人已经与我们并肩工作的不同方式。例如，当我赶往德州的航班时，我在希思罗机场看到一台大小如垃圾桶的地面清洁机来回扫地。一对年长的夫妇在它驶过时停下来指着看，但大多数旅行者都对它视若无睹。然后，到达奥斯汀后，我路过一台“机器人咖啡师”在制作咖啡。那台机器更像是一场纯粹的表演：机器人只是一个机械臂，将杯子放在机器出水口下方。在这里，我想到了机器人学的两条脉络：一是有用且无形的，另一是戏剧化且多余的。
T here is a basic challenge in robotic design that I’ve come across time and time again. I refer to it as the dishwasher problem. It’s like this: Imagine you’re designing a robot to clean and dry dishes the way a human does. Think of all the difficulties you need to overcome: Your robot needs hands and arms that can manipulate items of different shapes and sizes, and a vision system to identify muck and grime. It needs to be strong enough to grasp slippery things, sensitive enough to handle breakables, and dexterous enough to clean the insides of items like mugs and graters. Alternatively, you could build a wate rproof box, fill it with jets and sprays, and stuff everything inside. That’s a much simpler way to tackle the problem, and one that has gifted humanity the dishwasher.
在机器人设计中，我一次又一次遇到一个基本难题。我称之为“洗碗机问题”。情况是这样的：想象你正在设计一台像人类那样清洗和擦干餐具的机器人。想想你需要克服的所有困难：你的机器人需要能够操纵各种形状和大小物品的手和手臂，需要一个能够识别污垢和油渍的视觉系统。它需要足够强壮以抓握滑溜的东西，足够灵巧以处理易碎品，并且足够灵活以清洁像杯子和刨丝器内部这样的物品。或者，你可以造一个防水的箱子，装上喷嘴和喷水装置，把所有东西都塞进去。这是一种更简单的解决问题的方式，也正是洗碗机带给人类的礼物。
Criticism of humanoids within the robotics industry often follows a similar logic. Why go to all the trouble of mimicking nature’s blueprints when our own designs can do the job more efficiently? We don’t make planes that fly by flapping their wings or ships that wriggle through the water like tuna. So why make things harder for ourselves?
在机器人行业内，对类人机器人的批评常常遵循类似的逻辑。既然我们自己的设计可以更高效地完成任务，何必费尽心思去模仿大自然的蓝图？我们不会制造通过挥动翅膀飞行的飞机，也不会制造像金枪鱼那样在水中扭动前进的船只。那么，为什么要自找麻烦呢？
The answers engineers have given me vary from the spiritual to the pragmatic. The more philosophical among them point out that humans have been making simulacra of our bodies for millennia. There are four-thousand-year-old “living statues” from ancient Egypt that operate by string, for example, while in the Renaissance, humanoid automatons were a novelty for the rich: courtiers made with wooden gears posed for audiences and played the flute. Such history implies that building humanoids is a cultural imperative, an instinct that parallels biological reproduction. But most engineers tend to be more practical. The world is built for humans, they say. Our environment is full of steps and handles for feet and hands, so any machine meant to operate alongside us must possess the same features.
工程师们给我的答案从精神性的到务实性的各有不同。比较哲学化的人指出，人类制造身体仿制品的历史可以追溯千年。例如，古埃及有四千年历史的“会动的雕像”，通过绳索运作；而在文艺复兴时期，人形自动机是富人的新奇玩物：由木质齿轮制成的宫廷人偶会为观众摆姿势并吹奏长笛。这段历史意味着制造人形机器人是一种文化必然，一种与生物繁衍相似的本能。但大多数工程师往往更为务实。他们认为，世界是为人类建造的。我们的环境充满了供脚和手使用的台阶与把手，因此任何旨在与我们并肩工作的机器都必须具备相同的特征。
Mindar, a humanoid that delivers Buddhist sermons, at the Kodaiji Temple, in Kyoto, Japan, 2019. The robot was developed by roboticists at Osaka University in collaboration with the temple’s staff.
Mindar，一款在日本京都高台寺宣讲佛法的人形机器人，摄于 2019 年。该机器人由大阪大学的机器人学家与寺庙工作人员合作开发。
Makr Shakr robot bartenders at Planet Hollywood, in Las Vegas, 2017. The Makr Shakr robot was created by Carlo Ratti, the director of the MIT Senseable City Lab; the Coca-Cola Company; and Bacardi Rum.
2017 年拉斯维加斯好莱坞星球（Planet Hollywood）的 Makr Shakr 机器人调酒师。Makr Shakr 机器人由 MIT 可感城市实验室（Senseable City Lab）主任 Carlo Ratti、可口可乐公司（The Coca-Cola Company）和百加得朗姆酒（Bacardi Rum）共同创建。
The RBO Hand 3 robot holds a flower in Berlin, 2019. The robot was developed in the Robotics and Biology Laboratory at Technische Universität Berlin.
2019 年柏林，RBO Hand 3 机器人在手中握着一朵花。这款机器人由柏林工业大学（Technische Universität Berlin）的机器人与生物学实验室（Robotics and Biology Laboratory）开发。
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Jonathan Hurst, the co-founder and chief robot officer at Agility Robotics, makes a more fundamental claim. Even if you were to start from scratch when designing a machine to handle human labor, he says, you would still end up re-creating the Homo sapiens blueprint simply as a matter of convergent evolu tion. Form must follow function, and if that function is to replace humans, it helps to be human-shaped.
Agility Robotics 的联合创始人兼首席机器人官 Jonathan Hurst 提出了一个更为根本的论断。他表示，即便在设计一台用来替代人类劳动的机器时从零开始，你最终仍然会出于趋同进化的原因重新创造出与智人（Homo sapiens）相似的蓝图。形态必须服从功能，而如果功能是取代人类，具有人形外形会更有帮助。
Take, for example, warehouse work, which is usually seen as the beachhead for humanoids owing to its relative simplicity and recruitment challenges. Unless you want to completely redesign your warehouse, you need to build machines that are able to navigate between tightly packed shelves while also lifting and grabbing objects, and that can maintain their balance while their center of gravity shifts from high to low. If you were taking a simple approach, you might design something resembling a coatrack on wheels, with platforms that move up and down along a central tower. But for that machine not to topple over when it lifts a heavy object to an upper shelf, it would need a large base that would make it much less maneuverable. The best solution for this work, Hurst and others argue, is a bipedal, bimanual robot that can turn on the spot and adjust its center of gravity while carrying heavy items. Even the addition of a robot “head” makes sense, as you need to put cameras and sensors somewhere high to oversee the work. As Hurst puts it: “We’re not copying a person. We’re doing it for actual reasons.”
以仓库工作为例，这通常被视为人形机器人登陆的前沿阵地，因为这类工作相对简单且招工困难。除非你想彻底重新设计仓库，否则需要制造能够在密集排列的货架间穿行、能够举起并抓取物品、并且在重心从高到低变化时保持平衡的机器。如果你采用简单的方法，可能会设计出类似带轮衣架的东西，带有沿中央立柱上下移动的平台。但为了让那台机器在把重物举到上层货架时不倾倒，它需要一个很大的底座，这会使它变得难以机动。赫斯特和其他人认为，这类工作的最佳解决方案是双足双臂的机器人，它能原地转向并在搬运重物时调整重心。即便加一个机器人“头”也是合理的，因为需要把摄像头和传感器放在较高位置以监控工作。正如赫斯特所说：“我们并不是在复制一个人。我们这么做是有实际理由的。”
As I walk around Apptronik’s factory, I watch engineers fit together the pieces of this human puzzle. There are racks of arms and shelves of legs, metal gears hanging from hooks, and trays of actuators ready to be assembled. At one table it looks as though an anatomy lesson is taking place. The limbs, head, and chest of an Apollo unit have been deconstructed and laid flat, with its wires and cables teased apart like muscle and nerves. As I watch, an engineer activates the array, and the limbs, fixed to the table, start to twitch in place. I’m reminded of his torical accounts detailing the first experiments with electricity, when scien tists used rudimentary batteries to make the legs of dead frogs spasm, believing that the mysterious force they’d discovered might be the animating principle of life itself. Watching Apptronik’s engineers gathering around their creation, I feel a similar sense that the numinous is at work. Not many in the robotics industry claim to be playing God, but at times the sheer ambition of the work transcends simple engineering.
当我在 Apptronik 的工厂里四处走动时，我看着工程师们把这个人的拼图各个部分装配起来。架子上摆着一排排手臂，货架上放着一排排腿，金属齿轮挂在钩子上，托盘里放着待组装的执行器。在一张桌子旁，看起来仿佛在上解剖课。一个 Apollo 单元的四肢、头部和胸腔被拆解并摊开，电线和电缆像肌肉与神经一样被理开。我观看时，一名工程师激活了这组装置，固定在桌上的四肢开始原地抽动。这让我想起有关早期电学实验的历史记载，当时科学家用简陋的电池让死青蛙的腿痉挛，认为他们发现的这种神秘力量可能就是生命的驱动力。看着 Apptronik 的工程师们围拢在他们的创造物周围，我也产生了类似的感觉——一种神秘力量在起作用的感觉。机器人行业里没有多少人会声称自己在扮演上帝，但有时这项工作的宏大雄心超越了单纯的工程学。
Though Cardenas acknowledges the practical reasons for building humanoids, his own motivation goes further. It’s not just about making machines fit our environment, he said, but radically transforming the type of work they can perform. It’s about changing what a robot is*.* Traditional industrial machines, he explained, are static, expensive, and dangerous. These are the sorts of robots you see assembling cars in B-roll footage on the news: huge mechanical arms administering spot welds and paint jobs with unimpeachable rigor and precision. But the robot of the future, Cardenas says, is a different beast. Thanks to its AI training, it doesn’t rely on detailed instructions but is responsive and dynamic, able to recognize tools and environments and follow natural-language commands. It’ll cost as much as a sedan, work safely alongside us, and because it’s shaped like a human, it’ll do whatever we can. “We believe that the humanoid is like the personal computer,” he says. “It will be the robot that has the highest potential to scale.”
虽然卡德纳斯承认制造类人机器人的实用原因，但他的动机更进一步。他说，这不仅仅是让机器适应我们的环境，而是彻底改变它们能执行的工作类型。这是关于改变机器人的定义。他解释说，传统的工业机器是静态的、昂贵的且危险的。这类机器人就是你在新闻片段中看到的组装汽车的那种：巨大的机械臂以无可指责的严格和精确进行点焊和喷漆。但卡德纳斯所说的未来机器人则是另一种存在。得益于其人工智能训练，它不依赖详尽的指令，而是具有响应性和动态性，能够识别工具和环境并遵循自然语言指令。它的价格将相当于一辆轿车，能在我们身边安全工作，并且因为它具有人的形态，就能做我们能做的任何事。“我们相信类人机器人就像个人电脑，”他说。“它将是最有潜力实现规模化的机器人。”
Later, as we sip coffee and talk more about Apptronik’s plans in the conference room, Cardenas begins to shift into a mode of utopian reasoning that you often hear in the tech world. Until then, he’d been practical, explaining actuators and motors, but now he was navigating a realm where numbers multiply frictionlessly and progress is inevitable. “Let’s say, on the whole, for every average person, fifty years from now, robots give you five years of improved quality of life,” he says. “Five years of improved life per person is forty billion years of collective energy that you could pour back into the sum total of the human experience. What do we do with a billion years, let alone forty billion?”
后来，当我们在会议室一边喝咖啡一边更多地讨论 Apptronik 的计划时，Cardenas 开始转入一种你常在科技界听到的乌托邦式推理模式。在那之前，他一直很务实，解释驱动器和电机，但现在他在一个数字无摩擦倍增、进步不可避免的领域里航行。“假设总体上来说，对于每个普通人，五十年后，机器人能为你带来五年改良的生活质量，”他说。“每个人五年改良的生活就是四百亿年可以重新注入到整个人类体验总和中的集体能量。我们用十亿年能做什么，何况四百亿年？”
I nod along, aware that engaging too closely with these arguments was hardly what he wanted. I think to myself: This is the real draw of the humanoid. It is mystical. It stokes the imagination, just like in earlier ages, for if we can replicate ourselves without defects, what can’t we achieve? The notion clearly motivates Cardenas, instilling in him a sense of fervor and urgency. As our meeting wraps up and his PR team tries to drag him to his next appointment, he can’t stop talking—he’s halfway out the door before he sticks his head back in the room to make one last point, to try and make me see. “As humans, we have conceived of humanoids longer than we’ve conceived of computers,” he says. “To me, the story is: Wow, all this time we’ve been thinking about this. Now here we are at the front end of it.” He stops, hand on the doorframe, then asks aloud the questions that plainly occupy him: “Where does it go? What does that look like?” He stares past me as if into some unknowable future, then smiles, shrugs, and walks back into the factory.
我点头附和，明白过于深入参与这些论辩并不是他所想要的。我心想：这正是类人机器人的真正吸引力。它带有神秘感，激发想象，就像早先的时代一样；因为如果我们能无瑕地复制自己，还有什么是我们做不到的？这一观念显然激励着卡德纳斯，赋予他一种热忱和紧迫感。我们的会面结束，他的公关团队试图把他拉去参加下一个约会时，他还停不下来——他半只脚已经迈出门外，却又把头伸回房间，最后再说上一句，试图让我看见。“作为人类，我们对类人的构想比对计算机的构想更早，”他说。“对我来说，故事是：哇，这么久以来我们一直在思考这个。现在我们就在它的前端。”他停下，手扶着门框，然后大声问出那些显然萦绕在他心头的问题：“它会走向何方？那将是什么样子？”他凝视着我身后，仿佛望向某个不可知的未来，随后微笑、耸肩，走回了工厂里。
I n the genesis myth of ancient Sumer, the gods made humans with a clear, if depressing, purpose: to be their servants. Once molded from clay, the first humans tilled the fields, built temples, and provided sacrificial lambs for the pantheon’s delight. Advocates of our robot future have similarly mundane plans for our mechanical progeny. They’ll work in fields, factories, and warehouses, of course, but just as in the Sumerian creation story, they’ll also wait on us, following a cultural tradition of robot butlers from Rosey the Robot in The Jetsons to Robin Williams’s noble robo-servant Andrew in Bicentennial Man. Even today, the robot butler is shorthand for the elusive Good Timeline, emblem of a future in which the luxury of household staff is made accessible and ethical thanks to the wonders of technology.
在古代苏美尔的创世神话中，众神造人有一个明确而令人沮丧的目的：成为他们的仆人。首批人类从泥土中被塑成后，耕作田地、建造神庙，并为诸神的喜悦献上牺牲的羔羊。我们机器人未来的倡导者对机械后代也有类似世俗的安排。他们当然会在田间、工厂和仓库工作，但就像苏美尔的创造故事中一样，他们也会为我们服务，延续从《杰森一家》里的罗茜机器人到罗宾·威廉姆斯在《双百年人》（Bicentennial Man）中扮演的高贵机器人仆人安德鲁的文化传统。即便在今天，机器人管家仍然是难以捉摸的“美好时间线”的代名词，是一种象征：技术的奇迹使家庭雇佣人员的奢侈变得可及且合乎道德的未来。
No humanoid startup draws more heavily on this vision than 1X Technologies, a Palo Alto–based company founded by the Norwegian roboticist Bernt Børnich (who, according to Cardenas, is one of the industry’s “true believers”). Last year, 1X unveiled NEO, a “humanoid robot for the home” that is still in the prototype stage and undergoing testing in the homes of 1X employees. Instead of the industrial look favored by many rival robots, NEO is notable for its aggressively nonthreatening appearance. The machine is clad in a beige knitted bodysuit (this has the practical benefit of covering up pinch points, the gaps between joints liable to trap human fingers) and has a diminutive head fronted by a smooth black visor. In one promo video, NEO is shown performing household chores in minimalist homes, carrying laundry and pushing a vacuum cleaner while its owners do something inscrutable with an iPad. The overall mood is cozy, serene, and neutered: a weighted blanket for the robot world.
在所有类人的创业公司中，没有哪家比总部位于帕洛阿尔托的 1X Technologies 更深受这一设想影响。该公司由挪威机器人工程师伯恩特·伯尼奇（Bernt Børnich）创立，据卡德纳斯称，他是业界的“真正信徒”之一。去年，1X 推出了 NEO，一款“用于家庭的类人机器人”，目前仍处于原型阶段，并在 1X 员工家中进行测试。与许多竞争对手偏好的工业化外观不同，NEO 以其极力显得无害的外表而引人注目。该机器身着米色针织连体衣（这在实际使用上有遮盖夹点的好处——关节间的缝隙容易夹到人手指），头部小巧，前面是一块光滑的黑色面罩。在一段宣传视频中，NEO 在极简风格的家中做家务，搬运洗衣物并推动吸尘器，而其主人则用 iPad 做着让人难以理解的事情。整体氛围温馨、宁静且被“阉割”了：仿佛机器人世界的一条加重毛毯。
Børnich’s decision to build humanoids for the home hinges on the technical premise of the ChatGPT moment. If data is key to creating AI control systems, and if robot butlers are the end goal of the industry, then, Børnich says, they need to begin testing in these environments as soon as possible. This in itself is not crazy. Boston Dynamics, perhaps the most established and best-known robotics firm in the world, is building LBMs for its humanoid, Atlas, by collecting video and sensor data of robots doing things like slicing fruit or installing bike parts. The company’s robots are controlled remotely, either in virtual environments or in real life, using teleoperation systems. Training data is then used to create an AI model that can carry out these tasks autonomously. It’s similar to how a chess-playing AI is first trained on games played by humans, then uses this information to create its own strategies and moves. As Scott Kuindersma, a vice president of robotics research at Boston Dynamics, told me, “If you have a robot and a teleop system that you can use to repeatedly produce a behavior on the robot, then we basically have the technology to turn the crank and turn that into an autonomous policy.” But, he added, that doesn’t mean the robot will perform its task with perfect accuracy or reliability, and it certainly doesn’t mean robots are ready to be placed in the home.
博尼奇决定为家庭制造人形机器人，基于一个关于 ChatGPT 时刻的技术前提。如果数据是创造 AI 控制系统的关键，而机器人管家是这个行业的最终目标，那么，博尼奇说，他们就需要尽快在这些环境中开始测试。单就这一点来说并不荒唐。波士顿动力，也许是世界上最资深、最知名的机器人公司，正通过收集机器人切水果或安装自行车零件等操作的视频和传感器数据，为其人形机器人阿特拉斯构建学习型动作库（LBMs）。该公司的机器人通过远程操作系统在虚拟环境或现实中被远程控制。然后将训练数据用于创建能够自主执行这些任务的 AI 模型。这类似于象棋 AI 首先在由人类下的棋局上进行训练，然后利用这些信息生成自己的策略和走法。 正如波士顿动力机器人研究副总裁斯科特·奎德斯马（Scott Kuindersma）对我所说：“如果你有一台机器人和一个远程操控系统，能够反复在机器人上产生某种行为，那么我们基本上具备将这一过程机械化并把它转变为自主策略的技术。”但他补充道，这并不意味着机器人会以完美的精确度或可靠性执行任务，也绝对不意味着机器人已经可以被放到家庭中使用。
With AI in the form of chatbots, plausible mistruths and inaccuracies usually have a limited scope for harm, but with a domestic robot, mistakes could be catastrophic. Imagine you tell your machine butler, “Pour me a cup of tea,” and it pours boiling water into your baby’s sippy cup rather than your mug. Or you tell it, “Put my laundry in the washing machine,” and it grabs a hamper of clothes in which your cat is hiding and fires up the express cycle. There are obvious security and privacy concerns, too. Any robot in your home would have an array of cameras, microphones, and sensors, becoming an alluring target for hackers, while the robots them selves would need to be accessed re motely for troubleshooting, potentially giving attackers physical access to your house. For these and other safety reasons, skeptics in the industry allege that companies promising to deliver domestic robots in a matter of years are overly optimistic. “This is a very high uncertainty prediction for me,” Kuindersma tells me. His colleague, Marc Theermann, the company’s chief strategy officer, says: “I’m not sure if [we] even believe that humanoids in the home is a thing in the foreseeable future.”
以聊天机器人形式出现的人工智能，其可信度不高的虚假信息和不准确之处通常造成的伤害有限，但若是家用机器人，错误可能造成灾难性后果。想象一下，你告诉你的机器管家“给我倒杯茶”，它却把沸水倒进你婴儿的学饮杯而不是你的马克杯。或者你告诉它“把我的洗衣放进洗衣机”，它抓起装有躲在其中的猫的洗衣篮并启动了快洗程序。显而易见还有安全和隐私方面的担忧。家中的任何机器人都会配备一系列摄像头、麦克风和传感器，成为黑客的诱人目标，而这些机器人本身在远程故障排查时需要被访问，可能会让攻击者获得进入你家中的实际物理途径。基于这些及其他安全原因，行业中的怀疑者声称那些承诺数年内能交付家用机器人的公司过于乐观。“对我来说这是一个非常不确定的预测，”Kuindersma 告诉我。他的同事、公司首席战略官 Marc Theermann 说：“我不确定我们是否认为在可预见的未来家里会出现类人机器人。”
Because of the high-risk, high-reward nature of 1X’s plans, I’d been particularly keen to see NEO for myself. But the firm was frustratingly elusive. Communication was fragmented, my requests to visit the company’s headquarters were rejected, and a scheduled interview with Børnich himself was canceled at the last minute while I waited on the line. Such behavior tends to make a journalist only more determined, but when I traveled to San Francisco to visit 1X’s competitors and told the company’s representatives I was in the area, ready to chat anywhere, anytime, I was rebuffed for good. “Thanks again for the dialogue,” said the head of communications. “After careful consideration, we’ve decided not to move forward with the story at this time.”
由于 1X 计划属于高风险高回报型，我尤其想亲自看看 NEO。但这家公司令人沮丧地难以接触。沟通支离破碎，我要求参观公司总部的请求被拒绝，原定与 Børnich 本人采访在我在线等待时也在最后一刻被取消。这种行为往往只会让记者更加执着，但当我前往旧金山拜访 1X 的竞争对手并告诉该公司代表我正好在附近，随时可以聊时，我却被彻底回绝。“再次感谢你的沟通，”公关负责人说。“经过慎重考虑，我们决定此时不推进这篇报道。”
In my experience, when companies promising transformational new technology decline to show it to the press, it’s not a great sign. Thankfully, 1X does talk to some favored sources, mostly YouTubers and podcasters who focus on our bright technological future, so I can tell you that Børnich comes across as warm and friendly, with a goofy smile. He looks like a retired skateboarder, with long blond hair and a wardrobe of baggy T-shirts, and he makes big promises. “The future where you have humanoids at home folding your laundry is a lot closer than you think, and the price will also be a lot lower than most people imagine,” he says in one video from last August, promising that 1X “can manufacture [robots] at the cost of a relatively affordable car.” In another interview from 2024, he speculates about a world in which 1X builds “thousands of NEOs in 2025, tens of thousands in 2026, hundreds of thousands in 2027, millions in 2028.”
根据我的经验，当那些承诺带来变革性新技术的公司拒绝向媒体展示时，通常不是一个好兆头。值得庆幸的是，1X 会与一些受宠的媒体交流，主要是那些关注我们光明科技未来的 YouTuber 和播客主持人，所以我可以告诉你，Børnich 给人的感觉是热情友好，带着有点傻气的笑容。他看起来像个退休的滑板手，留着长长的金发，穿着宽松的 T 恤，且喜欢夸下海口。“拥有能在家为你叠衣服的人形机器人的未来，比你想象的要近得多，价格也会比大多数人想象的低得多，”他在去年八月的一段视频中这样说，并承诺 1X“能够以相对负担得起的汽车价格来制造[机器人]”。在另一段 2024 年的采访中，他设想了一个世界，1X 在“2025 年制造数千台 NEO，2026 年制造数万台，2027 年制造数十万台，2028 年制造数百万台。”
To stoke belief in the promise of humanoid butlers, 1X has relied heavily on carefully orchestrated promotional content. In a YouTube video by the San Francisco filmmaker Jason Carman, 1X brings a NEO unit to Carman’s house “to do chores.” The video, titled “I Lived with a Humanoid Robot for 48 Hours,” has nearly half a million views and shows the NEO making coffee for Carman. This might be impressive, but it’s unclear whether the robot is operating autonomously or being controlled by an engineer. The only task the machine performs on camera is pouring boiling water over coffee grounds. A 1X employee then takes the brewer, pours the coffee into a mug, and hands it to Carman. “NEO made it,” he says. “I swear.”
为了激发人们对类人管家前景的信心，1X 大量依靠精心策划的宣传内容。在旧金山电影制作人 Jason Carman 的一段 YouTube 视频中，1X 带着一台 NEO 设备到 Carman 家中“做家务”。该视频题为“我与一台类人机器人同住了 48 小时”，浏览量接近五十万，展示了 NEO 为 Carman 做咖啡。这看起来或许令人印象深刻，但并不清楚机器人是自主操作还是由工程师遥控。机器在镜头前唯一执行的任务是将沸水倒在咖啡渣上。随后一名 1X 员工拿起咖啡壶，把咖啡倒进杯子并递给 Carman。“NEO 做的，”他说。“我发誓。”
Pointing out that the robot didn’t actually make the coffee but merely poured water from one container to another feels churlish, like shouting at a children’s magician: “It’s up his sleeve!” And as AI advances, it will become even more difficult to discern the truth of such demos. For example, many humanoids can now perform cartwheels or other impressive feats of acrobatics, but these may be one-off stunts rather than samples of a larger repertoire. Jim Fan, director of AI at Nvidia, has compared these performances to those of a “blind gymnast,” lacking awareness of the environment. If you were to introduce an obstacle in a backflipping robot’s path, it would crash right into it. Being able to copy one aspect of human mobility doesn’t mean we’ve mastered all of the underlying principles, too.
指出这台机器人实际上并没有真正地泡咖啡，只是把水从一个容器倒到另一个容器，这种说法显得刻薄，就像对儿童魔术师大喊：“他把东西藏在袖子里！”而且随着人工智能的进步，辨别此类演示的真实性将变得更加困难。例如，许多人形机器人现在可以做侧手翻或其他令人印象深刻的杂技动作，但这些可能只是一次性的噱头，而不是更大曲目的一部分。Nvidia 的人工智能主管 Jim Fan 曾将这些表演比作“盲人体操运动员”，缺乏对环境的感知。如果你在一个会后空翻的机器人的路径上放置障碍物，它会直接撞上去。能够复制人类运动性的某一方面，并不意味着我们掌握了其所有的基础原理。
These demos also highlight another meaning of the “ChatGPT moment.” Just as many people ascribe human-level intelligence to ChatGPT because it can generate fluent speech, a capability we’d previously encountered only in conversations with conscious beings, we often imagine that humanoid robots are as physically capable as we are just because they possess similar bodies and can accomplish some of the same tasks. In both cases, though, the familiarity of appearances masks hidden limitations. “You see a robot making coffee, and people can make coffee, and the robot looks like a person, and you can easily extrapolate to all the other kitchenlike things the robot might be able to do,” Kuindersma tells me. “In reality, maybe the robot can literally only make this cup of coffee with this coffee maker.”
这些演示也突显了“ChatGPT 时刻”的另一层含义。正如许多人因为 ChatGPT 能生成流利的语句就把它归为具有人类水平的智能——这种能力此前我们只在与有意识的存在对话时遇到过——我们也常常仅因类人机器人拥有类似的人体形态并能完成一些相同的任务，就想象它们在体能上和我们一样强大。然而在这两种情况下，外观的熟悉感都掩盖了隐藏的局限性。“你看到一个机器人做咖啡，人会做咖啡，机器人看起来像人，你很容易就推断出机器人可能也能做所有其他厨房里的事，”Kuindersma 告诉我。“但实际上，也许这个机器人真的只能用这台咖啡机煮这杯咖啡。”
I n a back room at Stanford University, engineers have mocked up a bare-bones grocery store, complete with shelves, baskets, and a scattering of unlabeled cans. It reminds me of my nieces’ kitchen play set, where the fine details of reality have been smoothed away so as not to confuse developing minds. I watch a wobbly figure stamping around the shelves and filling up a basket of goods. It looks more stable than my nieces do, but not by a whole lot.
在斯坦福大学的一间后室里，工程师们搭建了一个简陋的杂货店模型，里面有货架、篮子和几罐没有标签的罐头。它让我想起侄女们的厨房玩具套装，现实的细节被抹平了，以免让正在发育的头脑感到困惑。我看着一个摇摇晃晃的身影在货架间踏来踏去，往篮子里装满商品。看起来它比我的侄女们站得更稳一些，但也没有好多少。
The robot doing the shopping is Digit, the creation of Agility Robotics. The company is not trying to make an omnicapable robot butler, but something more immediately useful: a warehouse worker that can perform the basic but essential labor of moving objects from point A to point B. The design of Digit reflects Agility’s pragmatic approach. It’s a humanoid, yes, but with inhuman touches that suggest utilitarian preferences. Its head is a flat white mushroom rather than a skull; its “legs” are digitigrade, with backward-facing knees that make it easier to squat while standing flush against a shelf; and its “hands” can be either plastic nubs or vicelike clamps.
那个去购物的机器人是 Digit，由 Agility Robotics 制造。该公司并不试图打造一台全能的机器人管家，而是想做一些更实用的东西：一个仓库工人，能完成将物体从 A 点搬到 B 点这种基本但必需的劳动。Digit 的设计反映了 Agility 的务实方法。它确实是类人的，但带有一些超乎寻常的设计，显示出实用主义的偏好。它的头是一个扁平的白色蘑菇形，而不是头骨；它的“腿”是跖行式的，膝盖向后，使其更容易在紧贴货架站立时下蹲；它的“手”可以是塑料小凸起，也可以是类似虎口的夹具。
Melonee Wise, Agility’s chief product officer at the time, is similarly restrained. She’s quiet and calm, with a neat bob of hair and unfussy glasses. She’s been in the industry for nearly two decades, having worked at the famed robotics incubator Willow Garage before co-founding Fetch Robotics, a startup that made autonomous mobile robots, or AMRs: small robots resembling coffee tables on wheels. Before humanoids, AMRs were the Next Big Thing, and after the usual cycle of hype and consolidation, they’ve actually proven themselves to be useful. In 2022, Amazon had more than half a million AMRs in its warehouses, working parallel to (though not necessarily alongside) its overtaxed human employees. As a result of her work with AMRs, Wise avoids framing humanoids as some sort of industrial panacea for every economic ill, from labor shortages to manufacturing bottlenecks. Instead, she presents them as what they are: a piece of hardware with its own drawbacks and affordances, like any other tool. “One of the biggest lessons I learned about commercializing technology is the technology part is easy,” Wise says. The hard part? “Making the technology usable.”
梅洛尼·怀斯（Melonee Wise），当时是 Agility 的首席产品官，也同样克制。她沉默而冷静，留着整齐的波波头，戴着不起眼的眼镜。她在这个行业已经工作近二十年，曾在著名的机器人孵化器 Willow Garage 任职，之后共同创立了 Fetch Robotics，一家制造自主移动机器人（AMR）的初创公司：这些小机器人看起来像带轮子的咖啡桌。在人形机器人出现之前，AMR 曾被视为下一个重大事物，经过一轮通常的炒作与整合周期后，它们实际上被证明是有用的。到 2022 年，亚马逊在其仓库中拥有超过五十万台 AMR，与其过度劳累的人类员工并行工作（尽管不一定是并肩）。由于她在 AMR 方面的工作，怀斯避免将人形机器人描述为某种能解决所有经济问题的工业灵丹妙药，从劳动力短缺到制造瓶颈。相反，她把它们按本来面目呈现：一种有自身缺点和可用性的硬件，就像任何其他工具一样。“我从商业化技术中学到的最大教训之一是，技术本身是容易的，”怀斯说。真正困难的是什么？“让技术变得可用。”
As I talk to Wise, I get a better understanding of the complexities of automating even simple tasks. She tells me about visiting a customer who wanted to use robots in the production of ball bearings. “So we’re watching this gentleman do the task,” she says. “The [bearings] go through a grinder and come out the other side. You’re supposed to pick them up and put them into the container. Then all of a sudden, I watch the gentleman who’s operating the machine go to a drawer, grab a rag, and wipe down the entire surface of the machine.” Wise asked if this was necessary. The worker said yes, of course: the machine gets gummed up. And just like that, she tells me, the task became more chal lenging to automate. Agility’s robots could move the bearings without a problem, but it would be trickier to teach them when it was time to wipe down the machine, or how to do so without human assistance.
当我与怀斯交谈时，我对将哪怕是简单任务实现自动化的复杂性有了更深的理解。她告诉我曾去拜访一位想在球轴承生产中使用机器人客户的经历。“所以我们在看这位先生做这项工作，”她说。“轴承经过磨床，从另一侧出来。你应该把它们捡起来放进容器里。然后突然间，我看到操作机器的那位先生走到抽屉边，抓了块抹布，把整台机器表面擦了一遍。”怀斯问这是否有必要。工人当然说是：机器会被黏住。就这样，她告诉我，这项任务变得更难以实现自动化。Agility 的机器人可以毫无问题地移动轴承，但要教它们何时擦拭机器，或者如何在没有人帮助的情况下完成擦拭，就更棘手了。
As with the deceptive home robot demos, there is a difference between the ideal version of a task and the messy reality of putting humanoids to work in commercial settings. It’s a telling fact that only three U.S. ro botics firms have made such deployments—Apptronik, Figure AI, and Agility—and even then, these are only pilot programs. In March of last year, Apptronik said Mercedes-Benz was “exploring potential use cases” for its machines but offered no details about how many robots were being tested or for how long. That January, Figure AI announced a partnership with BMW. Brett Adcock, the CEO, claimed that the company had “a fleet of robots” in operation. But a spokesperson for BMW later told Fortune that only a single robot was working in its plants. (Adcock threatened to sue the magazine for its reporting and did not respond to my own requests for comment.) Even Agility, despite its more realistic ambitions, has made slow progress. Last June, the company announced an agreement with warehouse operator GXO Logistics, but it seems to involve just two Agility robots. To put these figures in context: the International Federation of Robotics reports that some 4.2 million industrial robots are in operation globally, with more than half a million new machines installed annually. The claims by some humanoid-robotics companies that they will exceed these figures in a matter of years with unproven technology clearly don’t add up.
正如那些具有欺骗性的家用机器人演示一样，理想化任务版本与将类人机器人投入商业环境工作时的混乱现实之间存在差距。一个耐人寻味的事实是，只有三家美国机器人公司进行了此类部署——Apptronik、Figure AI 和 Agility——即便如此，这些也只是试点项目。去年三月，Apptronik 表示梅赛德斯-奔驰“正在探索其机器人的潜在使用场景”，但未提供正在测试的机器人数量或测试时长等细节。今年一月，Figure AI 宣布与宝马建立合作关系。首席执行官布雷特·阿德科克声称公司“拥有一支机器人舰队”在运行。但宝马的一名发言人随后告诉《财富》杂志，实际上只有一台机器人在其工厂工作。（阿德科克威胁要起诉该杂志就其报道进行法律行动，并未回应我本人提出的置评请求。）即便是目标更现实的 Agility，其进展也很缓慢。去年六月，该公司宣布与仓储运营商 GXO Logistics 达成协议，但似乎仅涉及两台 Agility 机器人。为将这些数字置于背景之中：国际机器人联合会报告称，大约有 4.全球有 200 万台工业机器人在运行，每年新增安装的设备超过 50 万台。一些人形机器人公司声称，他们在数年内凭借未经验证的技术就能超越这些数字，这显然说不通。
At Stanford, I spend some time watching Digit at work, after which I take a virtual tour of Agility’s headquarters in Oregon. I watch the company’s robots lift crates, grasp packages, and move loads. Agility’s representatives show me the company’s software, which displays a diagram of a factory or shop, with icons representing robots and worksta tions. Customers can then set up a working routine by clicking these pieces, like in a video game. You click to select a robot, click to pick up an object, click there to drop it off, and so on. Here, I thought, were the basic components of an automated workforce, seemingly ready to go, and yet confined to limited demonstrations or experimental settings.
在斯坦福，我花了一些时间观察 Digit 的工作，之后我又在虚拟中参观了位于俄勒冈的 Agility 总部。我看到该公司的机器人搬起箱子、抓取包裹并搬运货物。Agility 的代表向我展示了公司的软件，软件显示了工厂或车间的示意图，图上用图标表示机器人和工作站。客户然后可以像在电子游戏里那样，通过点击这些图标来设置工作流程。你点击选择一个机器人，点击去拾取一个物体，再点击在那里放下，诸如此类。在那一刻，我想，这里有一套自动化劳动力的基本组成部分，看起来已随时可用，但却被限制在有限的演示或实验环境中。
Wise acknowledges the challenges that remain—cost, reliabil ity, integration—but remains confident that the industry is on the cusp of major change. She saw this happen with AMRs, she says, and notes that a “big unlock” is coming, when humanoid robots are allowed to operate freely around humans (right now they’re constrained to caged “work cells” because of safety fears). “We believe by the end of 2026 we will have humanoid robots free-roaming in facilities with trained adults,” she says, at which point they’ll be able to slot into the workplace alongside humans. I think of Digit navigating Agility’s fake grocery store, and yes, there is a sense of plausibility, even of inevitability. Of course there will be robots in warehouses in a few years’ time, but I wonder what impact they will actually have on working life. They could be a liberating force, yes, but also could just as easily be another prop in scenes of human drudgery, as unexceptional as forklifts or barcodes. It’s likely they’ll be useful and frustrating in equal measure—sharing the burden of human work without ever seeming to diminish it.
怀斯承认仍然存在挑战——成本、可靠性、集成——但她仍然相信行业正处于重大变革的边缘。她说，她在自主移动机器人（AMR）身上也见证过这种变化，并指出当类人机器人被允许在人类周围自由活动时，会有一次“重大解锁”（目前它们由于安全担忧被限制在笼状“工作单元”内）。“我们相信到 2026 年底，我们将会有在设施内与受过训练的成年人一起自由漫游的类人机器人，”她说，届时它们就能与人类一道融入职场。我想到 Digit 在 Agility 的模拟杂货店中穿行，确实，这感觉既可行又带有某种不可避免性。当然，几年后仓库里会有机器人，但我想知道它们究竟会对工作生活产生什么影响。它们可能成为解放的力量，也同样可能只是人类苦差场景中的另一个道具，像叉车或条码一样平常。它们很可能既有用又令人沮丧——分担人类工作的负担，却看起来并不减少这份工作。
I t can be hard to imagine meaningful changes to the world you know, but it’s easier in unfamiliar places. Perhaps this is why, in my interviews with robotics experts, they keep on talking about the transformation that robots will create in China. It’s there, I’m told, that humanoid labor will truly come into its own, a prediction that seems to scare people as much as it excites them.
很难想象对你所熟知世界的重大改变，但在陌生的地方则更容易。也许这就是为什么在我与机器人领域专家的访谈中，他们不断谈论机器人将在中国带来的变革。有人告诉我，正是在那里，人形劳动力才能真正发挥作用——这一预测既令人生畏，又让人兴奋。
China first surpassed the United States in industrial robot density in 2022, with 322 machines per ten thousand employees compared with 274 in America, and the gap has only widened since. Beijing’s Ministry of Industry and Information Technology has made robotics a key part of its industrial strategy, and aims to increase robot installations to 500 units per ten thousand workers by the end of the year. A review of documents by Reuters in May found that the government allocated more than $20 billion to the sector over the previous year, with state procurement of humanoids and related tech increasing by a factor of forty-five.
2022 年，中国在工业机器人密度上首次超过美国，每万名职工配备 322 台机器，而美国为 274 台，此后的差距只增不减。北京的工业和信息化部已将机器人技术作为其产业战略的核心部分，目标是在年底前将每万名工人的机器人安装量提高到 500 台。路透社在五月对文件的审查发现，过去一年政府对该领域拨款超过 200 亿美元，国家对人形机器人及相关技术的采购增长了 45 倍。
The pace of development feels frenetic. Videos of Chinese robots performing martial arts and acrobatics are common on social media, while the Chinese robotics industry has organized a series of spectacles to show off its advances. In April, the city of Hangzhou hosted the first-ever robot kickboxing tournament, featuring several humanoid robots made by Chinese startup Unitree outfitted with gloves and protective headgear, operated by humans with video-game controllers. (The robots were more Rock ’Em Sock ’Em than trained martial artists, but still put up a good fight.) Then, in August, Beijing hosted the World Humanoid Robot Games, with more than 280 teams participating in twenty- six different events, including soccer, boxing, and the long jump. Again, the bots were not always gainly—one viral video showed a humanoid veering off a running track and knocking over a human spectator—but the atmosphere was one of dynamism and experimentation. Here, robots were running free, if sometimes a little too literally.
发展节奏显得狂热。中国机器人表演武术和杂技的视频在社交媒体上很常见，而中国的机器人产业也组织了一系列盛会来展示其进展。四月，杭州举办了首届机器人踢拳赛，参赛者包括几台由中国初创公司 Unitree 制造的类人机器人，穿戴手套和护头，由人类用电子游戏手柄操控。（这些机器人更像“敲击玩具”而非训练有素的格斗家，但仍然打得有来有回。）随后在八月，北京举办了世界类人机器人运动会，超过 280 支队伍参加了包括足球、拳击和跳远在内的 26 个不同项目。同样，这些机器人并不总是优雅——一段病毒式传播的视频显示一台类人机器人偏离跑道并撞倒了一名现场观众——但现场氛围充满活力与试验精神。在这里，机器人被放开了束缚，尽管有时过于字面意义上的放开。
Like other Chinese industries, the country’s robotics sector benefits from economies of scale and generous state investment. “China will just manufacture everything, and the state backs it. So the volumes that they can produce are kind of absurd,” says George Chowdhury, a robotics analyst at ABI Research. The proximity of supply chains is also vital. U.S. companies looking to iterate on a new design often have to ship components back and forth to manufacturers in Asia. Chinese firms, on the other hand, can simply head to the factory next door, tweak things in person, and have new prototypes ready to test in a matter of days—the same reason China has dominated in high-tech markets like solar power, electric vehicles, and drones. “Drones and EVs aren’t easy to build—or, they weren’t at the time,” Reyk Knuhtsen of the market-research firm SemiAnalysis tells me. But Chinese manufacturers have been able to solve technological challenges by “brute-forcing the problem, just producing over and over and over until you figure it out.” Knuhtsen claims the same will be true of humanoids.
像中国的其他行业一样，该国的机器人产业受益于规模经济和慷慨的国家投资。“中国会把所有东西都制造出来，国家给予支持。所以他们能生产的数量有点离谱，”ABI Research 的机器人分析师乔治·乔杜里说。供应链的接近性也至关重要。希望对新设计进行迭代的美国公司常常不得不将零部件来回寄送到亚洲的制造商那里。另一方面，中国公司只需走到隔壁的工厂，亲自调整，几天内就能准备好新的原型进行测试——这也是中国在太阳能、电动汽车和无人机等高科技市场占据主导地位的同一原因。“无人机和电动汽车并不容易制造——或者说，当时并不容易，”市场研究公司 SemiAnalysis 的雷克·克努特森告诉我。但中国制造商能够通过“强力攻关，不断重复生产，直到弄明白为止”来解决技术难题。克努特森声称，类人机器人也将会如此。
The United States, however, still retains an edge in product quality and software. According to people who deal with the technology firsthand, it produces reliable machines that are more easily integrated into the workplace. Robert Stokes, who runs a robot distributor that sells Chinese bots to U.S. customers, says that “a good twenty percent” of the robots he buys from Unitree arrive broken, requiring repairs even before they’re up and running. The company’s marketing can also be misleading, he warns, with its robots unable to perform the stunts you see on social media without significant modification. “You’ve got a lot of development you have to do personally,” he says. “When a new robot is released, the software tools are initially rudimentary.” And even if you can make a robot dance, it doesn’t always mean you should. Stokes gives the example of Unitree’s G1 humanoid robot, which can be seen performing backflip after backflip in promo videos. In real life, he says, all these gymnastics quickly wear out the machine’s components.
然而，在产品质量和软件方面，美国仍然保持优势。据直接接触这项技术的人士称，美国生产的机器可靠性更高，更容易整合进工作场所。经营一家向美国客户销售中国机器人分销商的罗伯特·斯托克斯表示，他从 Unitree 购买的机器人中“大约有百分之二十是坏的”，在投入使用前就需要维修。他警告说，该公司的营销也可能具有误导性，其机器人在没有重大改造的情况下无法完成社交媒体上看到的那些特技。“你必须亲自做大量开发，”他说。“当一款新机器人发布时，软件工具最初都是粗糙的。”即便你能让机器人跳舞，也并不意味着你应该这么做。斯托克斯举了 Unitree 的 G1 类人机器人为例，宣传视频中它一个接一个地完成后空翻。他说，现实中所有这些体操动作会很快磨损机器的组件。
Still, Stokes is bullish about Chinese robots. The quality is improving rapidly, he says, and demand is growing. At the start of this year, he sold fewer than ten humanoids a month, but predicts this figure will rise to a hundred units next year. He compares the market to that of smartphones. The American robotics firms are copying Apple’s playbook, focusing on designing a few high-quality products, but Chinese companies are mimicking the Android ecosystem, pushing out high volumes in a range of designs. “The Apple approach is fine,” says Stokes. “But there’s a certain part of the market that needs the lower-end option.”
尽管如此，斯托克斯对中国机器人持乐观态度。他说，质量正在迅速提高，需求也在增长。今年年初，他每月出售的类人机器人不到十台，但他预测明年这一数字将上升到一百台。他将市场比作智能手机市场。美国机器人公司在复制苹果的做法，专注于设计少量高质量产品，而中国公司则模仿安卓生态系统，在各种设计上大量推出产品。“苹果的做法没问题，”斯托克斯说，“但市场上有一部分确实需要低端选项。”
Naturally, the same technological challenges facing humanoids in the United States apply in China as well, though these considerations are increasingly overshadowed by geopolitics. Chowdhury says that there is a growing cadre in government and industry who have bought into the hype around humanoids and believe that the world economy will be dominated by whoever cracks the problem first. “If China can print its own workforce, then you’re kind of in trouble economically, right?” he says. “It becomes almost an existential thing. It’s almost a cold war ramping up, I think, in the minds of some people.”
自然地，美国类人机器人的那些技术难题在中国同样存在，不过这些考量正日益被地缘政治所掩盖。Chowdhury 表示，政府和产业界中有一批越来越多的人相信关于类人机器人的炒作，认为谁先攻克这一难题，谁就将主导世界经济。“如果中国能打印出自己的劳动力，那么在经济上你就有点麻烦了，对吧？”他说。“这几乎变成了一种生存性问题。我想，在某些人心中，这几乎就是一场冷战的升级。”
When I talk with Knuhtsen about a future in which China and the United States have cranked up production and humanoids work as well as humans do for 65 tril lion market and replace all human labor, he says. “Coming out of my mouth, I hate that. I don’t want to be the guy saying that. But effectively that’s what’s in store, should it go correctly.”
当我与 Knuhtsen 谈到这样一种未来：中美两国大幅提高产量，人形机器人像人类一样工作，单价为 7000 美元时，他对自己预测的规模持谨慎态度。他所描述的最极端情形是，机器人将成为一个 65 万亿美元的市场并取代所有人类劳动。“从我口中说出来，我很讨厌那样。我不想成为那个说这话的人。但实际上，如果一切顺利，事情很可能会朝那个方向发展。”
This would create a workforce that is not only cheap, but also pliant and obedient—an appealing notion for elites who find it challenging to deal with human workers. It’s no coincidence, for example, that Musk, one of robotics’ biggest boosters, frequently decries the presence of unions in his factories. If only these troublesome humans could be automated, it would free the holders of capital from their obligations to the working class. And if workers can no longer withhold their labor as leverage, then the provision of social goods like housing and health care becomes discretionary. This would be a seismic change in the world’s social dynamics, regardless of which country gets there first. Musk has said he believes “we’re headed to a radically different world” with humanoids, but the extent of the change—and who it will benefit— is far from clear.
这将创造出一支不仅便宜，而且柔顺听话的劳动力——对那些难以应付人类工人的精英阶层来说，这是一个很有吸引力的设想。例如，作为机器人学最大支持者之一的马斯克，经常谴责他工厂中工会的存在，这并非巧合。如果这些麻烦的人类可以被自动化取代，那将使资本持有者摆脱对工人阶级的义务。而且如果工人无法再通过罢工等方式以劳动作为筹码，那么像住房和医疗这样的社会福利就会变为可随意决定的事项。无论哪个国家先实现，这都将是对世界社会动态的巨大冲击。马斯克曾表示他相信有了类人机器人“我们正走向一个截然不同的世界”，但这种变化的程度——以及将惠及谁——仍远不清楚。
As I talk with analysts about these possible outcomes, there’s something in our discussions that reminds me of Pascal’s wager. It’s a situation where the potential consequences are so extreme—in this case, a robot takeover of the global economy—that you’re compelled to take them seriously, despite their improbability. But frankly, it just doesn’t seem credible to me that robots will dominate the world’s economy within only a few decades. (Over a longer time frame, widespread adoption feels significantly more plausible.) Knuhtsen recognizes the unsettling scale of his forecasts. He describes his work, at times, as “looking into the abyss,” and it strikes me that there’s something hypnotic about contemplating change of this kind. It’s millenarian: a rapture for workers. You encounter these kinds of predictions from AI doomers, who warn about the threat posed to humanity by superintelligence. Often, they’re so entranced by the scale and drama of their claims that they lose sight of their implausibility. When playing God, it’s hard to stay grounded.
当我与分析师讨论这些可能的结果时，我们的讨论中有些内容让我想起了帕斯卡尔的赌注。这是一种情形，潜在的后果极端——在这里，是机器人接管全球经济——以至于尽管这种情况不太可能，你仍被迫认真对待它。但坦率地说，我实在难以相信机器人会在仅仅几十年内主宰世界经济。（在更长的时间范围内，广泛采用显得更有可能。）克努森意识到他预测的令人不安的规模。他有时把自己的工作形容为“凝视深渊”，让我觉得沉思此类变革有某种催眠感。这是末世论式的：对工人的一种狂喜。你会从 AI 末日论者那里遇到这类预测，他们警告superintelligence.对人类构成的威胁。往往，他们被自己主张的规模和戏剧性所迷住，以至于看不见这些主张的不可信。当扮演上帝时，很难保持脚踏实地。
B ack home in London after shaking hands with robot ambassadors, I’m still uncertain about the future of humanoids. Then, one of my contacts pings me about an upcoming conference in town: a meeting of various industry players talking through the fine details of putting robots to work. I dutifully sign up and head over to Hammersmith, arriving at one of those hotels that seem to exist outside local geography and function solely as gathering places for men and women in lanyards. As I dodge demonstrations of wheeled and legged robots, I hear chatter about motors and actuators, import taxes and safety standards, and the difficulty of getting these things to do what they’re supposed to.
回到伦敦，在与机器人大使握手之后，我对类人机器人的未来仍然感到不确定。随后，我的一个联系人给我发来消息，说城里将举办一场会议：各行业参与者将讨论让机器人投入工作使用的具体细节。我恭敬地报名参加，前往哈默史密斯，抵达一家仿佛不属于本地地理、仅作为佩戴证绶的人们聚会场所的酒店。当我躲开那些有轮子和有腿的机器人示范时，听到有人在谈论电机和执行器、进口税和安全标准，以及让这些东西按预期工作的难度。
Over the course of the conference, I dip in and out of talks from venture capitalists and startup execs. There are flashes of utopian speculation, but the event feels more grounded than my visits to Texas and California. Perhaps it’s simply the gloom that pervades all such industry get-togethers—the hotel carpet and the low-level anxiety. But there’s a reminder of history, too. In one talk, a researcher, Werner Kraus of Germany’s Fraunhofer Institute, notes that the industry has been here before, with so-called “collaborative robots”—small robotic arms designed to work safely alongside humans, and once thought to be the industry’s future. “We all have in mind how it went with the cobots twenty years ago,” he reminds the audience dourly, “when we said cobots would be the solutions for all our problems.” It didn’t work out that way. The promised cobot revolution never materialized, with high unit costs and hardware limitations confining them to relatively niche uses. At one point, in the smoking area, I chat with an entrepreneur from France who says he’s keen to start new robotics companies, but investors won’t commit. “It’s a mess,” he says. “VCs want to have a clearer understanding of the return. They don’t want to go full risk.”
在会议期间，我时而参加风险投资家和创业公司高管的演讲，时而退出。有些发言带着乌托邦式的臆想，但整体感觉比我去得德州和加州时更接地气。也许这只是所有此类行业聚会中弥漫的阴郁——酒店地毯和那种低层次的焦虑。但这里也提醒着人们历史的教训。在一次演讲中，德国弗劳恩霍夫研究所的研究员维尔纳·克劳斯指出，这个行业以前也走过类似的路，所谓“协作机器人”——那些设计成能在人体旁安全工作的微型机械臂——曾被认为是行业的未来。“我们都还记得二十年前协作机器人是怎么回事，”他沉闷地提醒听众，“当时我们说协作机器人会解决我们所有的问题。”事情并没有那样发展。所谓的协作机器人革命从未成真，高昂的单台成本和硬件限制把它们局限在相对小众的用途上。有一次，在吸烟区，我和一位来自法国的创业者聊天，他说自己很想创办新的机器人公司，但投资者不愿投入。“一团糟，”他说。 “风险投资家想更清楚地了解回报。他们不想承担全部风险。”
Later, I watch a talk delivered by Aaron Prather, the director of robotics at ASTM International. ASTM is a global standards agency, one of those unseen but essential components of the global economy that publishes more than thirteen thousand technical standards on everything from the proper viscosity of in dustrial lubricants to methods for decontaminating radioactive materials. Some standards are voluntary and others become law, but all contribute to the invisible framework that keeps the global economy from jamming up (or accidentally making you radioactive). Of course, Prather says, robots will have to meet certain standards, too.
后来，我观看了由 ASTM 国际机器人主管亚伦·普雷瑟（Aaron Prather）发表的一场演讲。ASTM 是一家全球标准机构，是那些不为人所见但对全球经济至关重要的组成部分之一，发布了一万三千多项有关各种技术标准，从工业润滑剂的适当粘度到放射性物质的去污方法。有些标准是自愿的，有些会成为法律，但所有这些都构成了防止全球经济卡壳（或意外让你受到辐射）的无形框架。当然，普雷瑟说，机器人也必须满足某些标准。
He runs through some of the haz ards that will need to be managed. There are the pinch points. There’s the need for “e-stops” (emergency stop buttons) and adaptations for the blind and deaf. And then there are the psychosocial impacts, too: managing the feelings we project onto these humanlike objects. “When we see something that looks like us, we expect certain things,” Prather says. “And when those expectations aren’t met, disappointment kicks in.” In other words, there are always more problems than we anticipate. He gives the example of stability tests like the one I conducted on Apollo. “We’ve all seen these videos, right? We’ve actually done some tests in that area and found that robots—humanoids—are doing really good on those.” But, he goes on to explain, there are other ways to knock a robot over, and what humanoids can’t currently withstand is a gentle, slow push. “No one’s testing for that,” he says.
他列举了一些需要应对的危险。有夹点。有需要设置“急停”按钮（紧急停止按钮）和为盲人、聋人进行的改装。然后还有心理社会方面的影响：我们赋予这些类人的物体的情感期待需要管理。“当我们看到看起来像我们自己的东西时，我们会期望某些事情，”普雷瑟说。“而当这些期望没有得到满足时，失望就会出现。”换句话说，问题总比我们预料的要多。他举了对阿波罗所做的稳定性测试作为例子。“我们都看过这些视频，对吧？我们实际上在那方面做过一些测试，发现机器人——人形机器人——在那些测试中表现得非常好。”但他接着解释说，还有其他方式可以把机器人推倒，而人形机器人目前无法承受的是温和、缓慢的推力。“没有人在测试这一点，”他说。
It’s a reminder of the unending complexity of a technology designed in our own image, though not necessarily a dispiriting one. Discussing these bureaucratic matters is itself a sign of maturity, and it’s clear from what I’ve seen that we’ve taken the next step in humanoid development. But from all my discussions, I’ve found that we can’t understand these machines by analogy alone. Just because ChatGPT became ubiquitous in a matter of months doesn’t mean that humanoids will follow a similar trajectory, and just because we’re replicating human anatomy doesn’t mean we’ve re-created human ability.
这提醒着我们：由我们自己形象打造的技术拥有无尽的复杂性，尽管这并非一定令人沮丧。讨论这些官僚事务本身就是成熟的表现，从我所见显然我们在人形发展上迈出了下一步。但通过我所有的讨论，我发现仅靠类比无法理解这些机器。仅仅因为 ChatGPT 在数月内变得无处不在，并不意味着人形机器人会遵循类似的轨迹；仅仅因为我们在复制人体解剖结构，也不意味着我们已经复现了人的能力。
After Prather’s talk, I stay in my seat in the main auditorium. The schedule tells me that next up is a mysterious “theatrical encounter,” which I presume will be some sort of dramatic turn starring humans and robots, a metaphor for our harmonious future with the machines. The lights in the room dim, and the stage is illuminated, revealing a human dancer in a sequined bodysuit posed next to a humanoid no bigger than a child. As Europop blasts from the speakers, the dancer performs cartwheels and backflips in the general vicinity of the robot, which at one point drops to the floor to crank out some push-ups. The lanyards and I watch impassively, and I think of Musk’s spandex-clad slideshow. After a few long minutes, the performance wraps up, and the dancer runs out through the aisles, exiting through the doors at the back of the hall. Left alone in the spotlight, the robot walks to the edge of the stage, waiting for its handlers, unable to manage the stairs.
普雷瑟的演讲结束后，我在主礼堂的座位上坐着不动。日程表上写着接下来是一场神秘的“戏剧性遭遇”，我猜大概会是某种以人类和机器人为主角的戏剧性表演，象征我们与机器和谐共处的未来。房间的灯光暗了下来，舞台被照亮，显现出一个穿着亮片连体服的人类舞者，旁边站着一个不比小孩大的类人机器人。随着欧洲流行音乐从扬声器中轰鸣，舞者在机器人附近翻筋斗和后空翻，机器人在某一刻趴到地上做俯卧撑。佩戴会务证的人和我面无表情地看着，我想到马斯克那穿着紧身衣的幻灯片。几分钟后，表演结束了，舞者穿过过道跑出去，从礼堂后方的门离开。被聚光灯单独留下的机器人走到舞台边缘，等着它的操控人员下台扶它，它自己无法应付楼梯。