Are Humanoid Robots Ready to Be Deployed?

On a recent sunny day in Silicon Valley, I visited the industrial headquarters of 1X Technologies. Security was tight, so I had to put a sticker over my cellphone’s camera and talk my way out of signing an N.D.A. before I was brought into an enormous space to meet Neo, the company’s home robot.

Neo stands five feet six and has no facial features except for two black cameras in place of eyes. The robot is a humanoid—its design is inspired by the human form—and its proportions are a blend of those of the median American male and those of the median American female. But Neo has no skin. Instead, it wears a beige nylon turtleneck bodysuit, gloves, and padded shoes over a see-through carapace. Under that is a skeleton made up of more than a hundred whizzing motors and cordlike artificial tendons that control Neo’s limbs. Neo’s cozy, minimalist aesthetic allows it to blend into the background. If it served me an espresso at a café, I’m not certain I would look up from my phone.

The robot weighs just sixty-six pounds, and I was able to pick it up in a bridal carry. It communicates through a speaker in its chest, using several different voices; the default one is in a calm but authoritative masculine register, an A.I.-modulated mixture of several voice actors. Neo can talk, listen, and respond to commands. In its skull is a squarish motherboard, roughly the size of a slice of bread and studded with white capacitors that look like teeth. This is Neo’s brain. Using A.I., it tries to translate your words into physical actions. If you ask Neo to pick up a cup from a table, Neo will attempt to pick up the cup. If you ask Neo to put the milk in the refrigerator, Neo will attempt to put the milk in the refrigerator. But Neo doesn’t always succeed at these tasks, and no one really knows what it can or cannot do.

The robot is the creation of Bernt Børnich, the C.E.O. of 1X Technologies. Børnich, a forty-two-year-old Norwegian, has been obsessed with robots since he was a child. His firm used to be called Halodi, and it sold wheeled security robots from offices south of Oslo. But in 2022 Børnich relocated to Silicon Valley, changed the company’s name, grew out his hair, and started wearing designer streetwear. Neo was announced shortly afterward.

Børnich believes in the supremacy of the human form. “We are incredibly well designed,” he has said. “I would argue this is kind of, like, why we won evolution.” The environment in which humanoids will operate is already built with able-bodied humans in mind. To open a door handle, you need a hand; to climb a flight of stairs, you need feet. Many roboticists are now working on humanoids, but Børnich takes biomimicry further than his peers: Neo uses tendons where other humanoids use motors, and Neo’s motherboard is in its head, while most humanoids have it stored in the chest. Børnich says humanoids have the potential “to do almost anything.”

Mention Neo—or Børnich—to other roboticists and you will be met with a slight pause. Børnich’s technical foundation is solid, but many people feel that he’s getting ahead of himself. Compared with the A.I. that generates language and images, the “physical” A.I. that runs a robot remains underdeveloped. “The world still doesn’t have a ChatGPT equivalent for a robot,” Deepu Talla, who oversees robotics at the microchip designer Nvidia, told me.

“I think home comes later,” Carolina Parada, the head of robotics at Google DeepMind, said. “I don’t think it’s a lack of interest, or even capability.” Rather, she explained, it was a question of safety. Jeff Cardenas, the C.E.O. of the industrial-humanoid manufacturer Apptronik, told me, “Around small pets, around small children, there’s still work to be done.”

Børnich agrees that Neo should not be used around small children. Still, he is keen to test consumers’ tolerance for what he calls “robotics slop”: tasks that are clumsily executed. For example, in a demonstration for the Wall Street Journal in October, Neo took longer than a minute to retrieve a bottle of water. Although Neo has a list price of twenty thousand dollars, more than ten thousand customers have already placed a deposit for one.

The customers are who you’d expect—wealthy early adopters from the Bay Area, Los Angeles, and New York City. Will DePue, a former OpenAI employee, lives in San Francisco with tech-enthusiast roommates. “I think our house has three orders on humanoid robots,” he told me. “This is kind of like the new iPhone.” Sometime later this year, workers at 1X’s factory, near Oakland, will pack a Neo into a container that looks like an oversized AirPods case, load it into the back of a truck, and deliver it to DePue’s residence. “Neo will probably not be a perfectly polished product, but at least it’s, like, an early version of what’s to come,” DePue said.

At 1X’s headquarters, my guide was Dar Sleeper, the head of product and design and Børnich’s informal second-in-command. Sleeper, who is twenty-seven, has already had a memorable career. After college, he joined the fashion brand Yeezy, then moved on to industrial design at Tesla. In other words, his first boss was Kanye West, and his second was Elon Musk. Børnich reminded him of Musk, Sleeper told me, if you “graft in some human empathy.”

In 2024, Børnich asked Sleeper to design a robot that didn’t scare children. Sleeper’s first attempt failed. “Basically, anyone under the age of a hundred was scared of it,” he said. (It had an eerily smooth black face.) His next iteration was better, but it still frightened children under the age of twelve. He added and removed facial features, experimented with skin textures, and went through hundreds of configurations of eye sockets. He settled, finally, on stripping as many features from Neo as he could, then covering it with soft textiles. “Even children under five seem to like it,” Sleeper said. “Babies are still scared, though.”

Sleeper led me through a labyrinthine industrial space at the headquarters. About eight hundred people work there, in roles involving assembly, testing, and research and development. We passed lathes, metal mills, and racks of 3-D printers, all in continuous operation. We passed a safety-testing zone, where technicians in goggles instructed robotic hands to karate-chop ripe cantaloupes. We passed Neo’s staging environments, which included a bedroom, a bathroom, a kitchen, and a dojo with tatami mats on the floor. We stopped at a motion-capture studio, where, off to one side, two dozen decommissioned models knelt together, as if in prayer.

“Yeah, I see it. I’m on my way as we speak.”

Cartoon by Ellis Rosen

This was where Sleeper had taught Neo how to walk. He told me that he had used his own body as the reference for Neo’s gait. (Sleeper stands well over six feet tall, with Vitruvian proportions.) Referring to his engineering co-workers, Sleeper said, “A lot of these guys walk like this,” then pantomimed a hunched scurry, his hands clutching imaginary backpack straps. “But I was an athlete in college,” he continued. “I actually had an anatomically perfect run.”

Sleeper puts the “bro” in tech bro. He played lacrosse at the University of Michigan, and, despite the controversies surrounding Kanye West, describes him as “one of the best creative geniuses of all time.” At one point, we were discussing a portable battery pack that Sleeper is designing for Neo. “It’s actually a nontrivial problem,” he told me. I asked him if he had ever used the word “nontrivial” before moving to Silicon Valley. “Probably not,” he said, and laughed. “I didn’t say a lot of shit before I showed up here.”

Sleeper has built a world around Neo. He oversees an in-house woodshop, which he uses to design sets, props, and furniture, all to mimic the environments that Neo will have to navigate. His plans for the 1X campus involve both a television studio and a forest. On the day of my tour, Sleeper wore a striking beige sweater, which he’d designed himself, in the style of Neo’s bodysuit.

I have been reporting on Silicon Valley for some while, which is another way of saying that I have been served a lifetime supply of bullshit. Before my visit to 1X, I had been ready to call bullshit on Neo, too. The company had posted some splashy videos on social media a few months earlier, then gone dark, and I suspected that Neo was just more overpromoted vaporware.

In fact, I was ready to call bullshit on the whole robotics industry. At the Las Vegas Consumer Electronics Show this January, there were numerous robots on display, from many manufacturers. They all seemed clunky and loud. They clanked when they walked. Sure, one robot landed a backflip—but then a piece of it broke off and flew toward the crowd. Nothing there seemed ready for consumer use.

But Neo was different. Neo was elegant. Neo was soft. Above all, Neo was quiet. With its padded feet and innovative tendons, it hummed along at twenty-two decibels, about the same volume as leaves rustling in a breeze. I felt a deep and horrible emotion triggered inside me, one familiar to any American—consumer lust. I wanted Neo in my house. I wanted it instantly, badly, immediately.

Sleeper took me to a demonstration kitchen, where Neo effortlessly slotted dishes into a wire rack. I was impressed by the robot’s dexterity and fluidity of motion. Then I noticed a tele-operator standing to the side, wearing a V.R. headset, holding controllers, and dictating Neo’s every move. The robot I was seeing was a marionette. 1X declined to show me a demonstration of the A.I. that will power Neo. Sleeper told me that previous versions of Neo had tended to fall over. 1X said that this problem had been resolved, but, when I asked Sleeper if the latest models always remained upright, he said, “To say it doesn’t fall is, like, a total stretch.” Still, when I asked if he believed 1X would meet its deadline for home delivery in 2026, he answered with no hesitation: “It’s a promise we’ve made to the world, and a promise we’ve gotta keep.”

Neo is one of a dozen humanoid robots scheduled to hit the market in the next twelve months. Its rivals include Figure’s 03 Humanoid, Boston Dynamics’s Atlas, and Apptronik’s Apollo. In January, Musk announced that he was converting a portion of a Tesla automotive plant in Fremont, California, into a robot-production factory, and hoped eventually to make a million Optimus robots there annually. His ultimate objective is to have robots working on the production line, making more robots, which he has called an “infinite money glitch.”

In China, efforts are equally ambitious. Unitree, based in Hangzhou, shipped more than five thousand of its G1 humanoids last year, making the company one of the world’s leading suppliers. The G1 stands about four and a half feet tall and has a hole in its head where a face would go. Its motors are loud, it clomps when it walks—it basically has no charm at all. Starting at around fourteen thousand dollars, it is also one of the more affordable advanced robots on the market, and, because it can run open-source software, it has become a favorite of academic robotics researchers. The G1 has also gained popularity with home-robotics enthusiasts—during the recent N.B.A. Finals, a G1 in a Knicks jersey attended watch parties outside Madison Square Garden.

I first encountered the G1 at the robotics lab of Aaron Ames, a professor of mechanical engineering at Caltech. Wearing a V.R. headset and holding controllers, I moved the robot back and forth a bit, then had it do some light calisthenics. It seemed shaky, almost drunk. I tried to make it clap its hands, but the G1 resisted. “Try it vertically,” a graduate student at the lab suggested. I did, and the robot pantomimed a delicate golf clap, without ever quite touching its hands together.

Later, in his office, Ames spoke for more than ten minutes, at a cadence of roughly two hundred words per minute, delivering a comprehensive takedown of 1X’s efforts. Ames believes that, no matter how sophisticated the engineering is, reliable A.I. for autonomous robots is years away. “I don’t know how 1X is actually going to get away with it,” Ames said. “I would worry about the legal ramifications when one of those robots falls on a person.”

Many industrial roboticists I spoke with were suspicious of the humanoid push. They told me that there are no standardized benchmarks for progress, and that videos of remarkable feats were often culled from hundreds of takes. In March, I talked with Modar Alaoui, a venture capitalist who invests in humanoid startups. He enthused about Iron, a robot from the Chinese manufacturer Xpeng, whose catwalk-inspired strut is so realistic that exhibitors have removed panels from its body to prove that it’s not a human in a robot suit. “Because of Xpeng’s work, I tell people not to work on locomotion anymore,” Alaoui said. “Locomotion is solved.” The day after I spoke to Alaoui, an Iron robot at a public demonstration at a mall in Shenzhen suddenly seized and fell over—it looked like it was having a stroke. The robot, which weighs more than a hundred and fifty pounds, could not recover, and three human handlers had to drag it away.

Accidents are not the only concern; Neo might also obey a malicious command. Imagine a young child asking Neo to bash its robotic head against the dining-room table. Guardrails installed in the A.I. would almost certainly prevent the robot from following the command, at least initially. But research shows that such guardrails can be circumvented. If the child were persistent enough (in the way that small children tend to be) and creative enough (in the way that small children tend to be) he or she might succeed in getting the robot to comply.

Robots can also be hacked. Last year, the security researchers Andreas Makris and Kevin Finisterre found a vulnerability in Bluetooth that would enable them to take control of a fleet of Unitree G1s, infecting one after another and “creating a robot botnet that spreads without user intervention,” they wrote. Humanoid robots need cameras and microphones to make their way through the world, which creates privacy concerns. Plus, their actions are unpredictable. “Babysitting these robots demands an entire operation team,” Jim Fan, a research scientist at Nvidia, wrote at the end of last year. “Mistakes are irreversible and unforgiving.”

Still, Parada conceded, putting robots in the home is “the ultimate dream.” Growing up in Venezuela, she fantasized about having a robot do her chores. Several roboticists I spoke with seemed a little disappointed by the current state of the field, compared with the expectations they’d had as children—nothing inanimate one day just started moving, nothing ever magically came to life. Sleeper recalled moments as a child when, he said, he “looked at stuffed animals, and got bummed out about how fucking lame they were.” Technology, he told me, sometimes made him sad: “It’s all just going into a screen, instead of into the world.”

After I left 1X’s offices, I took my first ride with the autonomous ride-sharing service Waymo. The Waymo was clean and quiet, and avoided a congested highway by navigating through side streets and frontage roads. But, after delivering me to my destination, the car turned in to a crowded In-N-Out Burger drive-through lane, which can take more than an hour to pass through. I laughed out loud, preparing to report on yet another epic A.I. fail—until the car executed a crisp three-point turn, escaped the line, and drove off.

I later learned that, in uncertain situations like this, a Waymo will sometimes request assistance from a human operator. Professional tele-operation “pilots,” working from the Philippines, oversee galleries of vehicle-camera feeds, alert for construction zones and lines of hungry Californians. Such pilots are also at work in other industries: in Japan, 7-Elevens do “autonomous” stocking using robot arms, which can be controlled from afar by workers wearing V.R. headsets. Human pilots also provide training data for A.I., and Waymo has used at least half a million hours of real-world data to fuel its autonomous-driving model.

A car merely has to avoid hitting things. A robot has to manipulate them without breaking them. 1X previously emphasized tele-operation in its marketing, but this generated pushback from potential customers. Now the company emphasizes A.I., but it hasn’t abandoned tele-operation: part of 1X’s gamble is that its customers will come to terms with the fact that a human might be peering into their home through Neo’s eye cameras. (DePue, the early adopter in San Francisco, told me that he would feel safer with a stranger tele-operating his robot than with a stranger cleaning his home.) Tele-operators will sit next to the A.I. team at 1X’s campus in Silicon Valley, and when the lighted rings on Neo’s earpieces change color customers will know that it is being remotely operated. “If you want a robot to bartend your party, we’ll get one of our operators,” Børnich said. “It’s also useful data for us.”

Data is to the A.I. revolution what coal was to the industrial one. A.I. communicates in discrete units of data called tokens. In language processing, a token might represent a few letters. In robotics, a token might represent a trajectory associated with a finger joint. But language models have the text of the entire open internet to learn from, not to mention the (uncompensated) copyrighted work of human authors, lifted from the dark web. There exists no equivalent repository—legal or otherwise—of motion trajectories for joints.

Cartoon by Edward Koren

One approach to this problem is to radically increase motion-capture efforts. The German robot developer Neura has put more than a thousand industrial workers in motion-capture suits, and is using these data to train humanoids. “Everyone is scared of a shitstorm, because it’s, like, ‘Oh, they’re replacing your work,’ ” David Reger, Neura’s C.E.O., told me. “It’s not! We’re getting, like, a lot of data.” This didn’t seem to address the job-loss question, so I pressed Reger on what would happen to the labor market if his efforts succeeded. He straightened his posture and insisted that, in the next few years, the U.S. would need these robots. “You will have a decrease of working labor, and then you will feel it,” he said. “Right now, you still don’t feel it, but in Europe, we feel it a lot. We think everyone disappeared somehow.”

Even if the entire population of Earth donned motion-capture suits, it would take decades to generate the amount of data that was used to train ChatGPT. Another approach is to train robots using videos from head-mounted cameras which have been posted on YouTube. With a little engineering magic, these “egocentric” videos can be turned into joint-trajectory data sets. More advanced video models might be able to extrapolate data from third-person views of real-world experiences such as sports games and cooking shows.

Some robotics companies don’t build hardware at all. Instead, they are focussed on helping existing robots navigate the physical world. About two and a half miles north of 1X’s headquarters, I visited the startup Skild AI. The two firms could not be more different. 1X’s robots are exquisite objects of high design. Skild’s lobby looked like an emergency room, with deactivated Unitree robots hanging from cranes and lying on tables. One was on a gurney; another sat in a wheelchair.

There, I met with Skild’s co-founders, Deepak Pathak and Abhinav Gupta, both professors at Carnegie Mellon University. If Sleeper and Børnich are confident marketers, Pathak and Gupta represent a different Silicon Valley archetype: the entrepreneur whose technological convictions lead him to ignore the pressure of public opinion. This was not the type of company that was going to plant a forest on campus.

Skild is attempting to build a “general purpose” physical A.I.: a single brain that can be slotted into any body. This brain should be able to control not just a humanoid but also a set of detached arms, a robot animal, or a wheeled cart. Pathak and Gupta have to stress-test these robots, so they spend a lot of time kicking them, punching them, and generally harassing them—at one point, they showed me a video of a man using a chainsaw to cut off the legs of a robotic dog. Within seconds, the dog began walking on the stumps.

I did not initially understand why Skild was treating its robots this way. (Nor did I understand why the chainsaw video was scored to hair metal.) Pathak explained that the ability to compensate for injury is one of the most important aspects of generalized physical intelligence. In Skild’s workshop were dozens of partially assembled robots, from a variety of manufacturers; one was wandering around without a head. Midway through the tour, we stopped in front of a robotic dog. One of its eyes was disabled, and its wiring was exposed; an employee was kicking it repeatedly. I was invited to join in.

“Kick it like how you would kick a human,” Pathak said.

“I wouldn’t kick a human,” I said.

“Don’t overthink it,” Pathak said.

After a moment’s hesitation, I planted my heel on the robot dog’s body and shoved it with force.The dog barrel-rolled across the showroom floor but was upright within half a second of coming to a stop.

Later, in a conference room, Pathak and Gupta explained that their seemingly cavalier attitude toward robot welfare was actually motivated by concern for human safety. (Better that a human kick a robot a thousand times than that a robot kick a human once.) Right now, they don’t think that humanoids are safe enough to use in residential settings—in fact, Pathak refuses to have one in his home. “People are using appearance as a way to misguide the public,” Pathak said. “If you make a robot humanlike, you expect it to have humanlike capabilities. But technology is far behind that.’ ”

Skild is one of the best-funded robotics startups, but much of its capital is spent on buying computing power from data centers. This is another way of saying that most of its money eventually goes to Nvidia. Nvidia, which has a five-trillion-dollar market capitalization, is the most valuable company in the world. In fact, adjusting for inflation, Nvidia may be the most valuable company in human history; its rival for the title is the Dutch East India Company. Jensen Huang, Nvidia’s C.E.O., has cosmic ambitions. “Wherever the universe has structure, we can turn that into A.I.,” he recently said.

Nvidia moved into robotics in 2014. Around this time, Huang recalls, he watched a neural network teach a robotic arm to shoot a hockey puck; he immediately calculated a rough estimate of the eventual size of the robotics A.I. market. Soon, Nvidia was touting virtual-reality simulators to train robots, and microchips to deploy in robot brains. (The simulators allow developers to experiment with surface friction, mimic faulty joints, and even alter gravity.) These early initiatives struggled at first, but Nvidia was able to establish what a former employee called “vender lock,” making robotics manufacturers dependent on it. Every single robot I encountered while reporting this article ran on an Nvidia microchip, and every single one had trained in an Nvidia digital gym.

Nvidia has also invested in many startups, including Figure, Neura, and Skild. This has produced accusations of “circular” dealmaking from skeptical investors, since Nvidia is providing funds to its own customers, who then use that money to purchase its hardware. Michael Burry, the investor made famous in “The Big Short” for betting against the housing market in the late two-thousands, today warns of “suspicious” revenues at many A.I. companies, including Nvidia. Huang has called such claims “ridiculous,” and defended the investments, saying that they are necessary to expand Nvidia’s “ecosystem.”

Nvidia’s robotics microchips are different from the ones they sell for A.I. training. They are “edge” chips, meaning that they do their processing in the robot instead of in a remote data center. The human brain uses about twenty per cent of the energy that the body generates; an Nvidia edge chip can drain as much as sixty per cent of a robot’s electricity supply. “It’s not the motors that take up most of the battery,” Cardenas, the C.E.O. of Apptronik, told me. “It’s actually the compute.”

But, if a robot needs more brainpower, it can draw it from a local server via Wi-Fi. A robot’s A.I., like most computer software, is regularly upgraded via the internet; robots get smarter every week. Most importantly, they have a hive mind. “Whatever one robot learns, the others all learn at the same time,” Børnich said.

This means that the wider the release of humanoids, the more skilled they become. If a thousand humanoid robots are sent to fold towels, they’ll learn from one another’s mistakes, and will adapt far faster than a single robot would. This network effect may account for 1X’s eagerness to get robots in the home. “There is definitely a data flywheel there,” Børnich said.

“Robot” is one of a small number of words that have entered the English language via Czech. (“Polka” and “howitzer” are others.) The term was first used in Karel Čapek’s play “Rossum’s Universal Robots,” from 1920. In the play, an industrial robotics conglomerate has transformed the world economy: robots do most of the work, and they are also deployed as soldiers. At the same time, the human birth rate declines to zero. Eventually, the robots take over, and kill almost everyone on Earth.

Any extended discussion of robots, I have found, will eventually reference the apocalypse. Even in more positive treatments, such as Isaac Asimov’s “I, Robot,” the androids end up taking over. When I broached the subject of the robot revolution with Børnich, I sensed a certain fatigue. “Look, they won’t seek revenge on us,” he said. “We can wipe their minds.”

Perhaps the fearful visions of Čapek—not to mention those of James Cameron, in his “Terminator” movies—have tainted the West’s cultural perception of robots. David Reger, Neura’s C.E.O., told me that American journalists ask him anxious questions about robots, but South Korean journalists just seem impatient. “They’re tired of waiting!” he said. “They ask, ‘When is it coming?’ ” Reger’s observation is supported by data. A Stanford University analysis of opinion polls across three dozen countries found that respondents in China, South Korea, Thailand, and Indonesia were the most excited about consumer applications of A.I. Respondents in the U.S. and Canada were the least.

Most of the roboticists I spoke with seemed more excited by the industrial applications of humanoid robots than by the prospect of their doing domestic chores. (“You’ll see them in McDonald’s first,” Rev Lebaredian, who runs physical A.I. simulation at Nvidia, said.) Apptronik’s Apollo humanoid—porcelain white, with knobby limbs and thick, sturdy legs—has been used in production at European automotive factories owned by Mercedes-Benz. For now, the robot is limited to activities such as picking out parts and loading conveyors. It needs to be fairly strong to complete this task, which means that a malfunction might hurt someone. For this reason, the robots are fenced off from the rest of the workers.

Humanoids make up only a tiny fraction of the five million or so robots currently deployed in factories worldwide. Mike Haley, a senior researcher at Autodesk, a maker of industrial-design software, has spent much of his career programming these specialized, non-humanoid factory bots. He told me that he has never seen a humanoid do anything useful in an industrial setting. Simpler robotics solutions, like detached arms for spraying paint, or autonomous forklifts for moving pallets, are more efficient, cost less, have fewer moving parts, and require less maintenance. “I truly believe that we have a moment a few years down the road from now where we look back at this humanoid thing and go, ‘Boy, that was bloody stupid,’ ” Haley said.

Commercial service robots are already commonplace in China, but these are cheap, special-purpose devices that deliver food or fold laundry. Expensive humanoids may not be needed for these tasks. At Skild, Pathak’s solution is to isolate a robot’s parts to fit the task at hand. “Let’s say you’re putting a robot in a factory like this, and you’re assembling something—should you really spend energy on the legs?” he asked. “I can separate the torso and put it on the table, then use the legs to carry something else.”

It seems that 1X is taking the Apple approach, designing beautiful products from scratch and controlling the entire manufacturing process. Skild is taking the Android approach, writing cross-platform software and running it on hardware made by other companies. Apptronik, Unitree, Tesla, and others—maybe they will be like Nokia, or Blackberry. Or maybe one of them will win.

About seven or eight million years ago, a branch of primates broke off and started developing superior brains, dexterous hands, and the capacity for language. That branch diversified into Australopithecus, and Ardipithecus, and Homo erectus. Eventually, Homo sapiens emerged and took over. Surveying the diversity of humanoid forms at this early stage of robotics, I could see something similar occurring. The essential form—two arms, two legs, a torso, and a head—was consistent, but there were many variations. Agility’s Digit has a square head and inverted kneecaps, like a grasshopper. Apptronik’s Apollo uses a classic sci-fi design, with digital readouts on its mouth and chest. Boston Dynamics’s Atlas has a toylike carapace and a glowing, hollow circle for a head. Tesla’s Optimus, Neura’s 4NE-1, and Figure’s 03 have all converged on similarly anonymous and ever so slightly sinister designs: white bodies with smooth black faceplates. One of these is likely the evolutionary ancestor of all that is to come.

The missing link might be the hand. The human hand is one of three pinnacles of hominid evolution, along with the brain and the voice box. It is by far the most capable manipulator in the animal kingdom, and can perform twenty-seven independent motions. Robotic hands lag far behind: we are years away from a robot that can both tie its shoes and shuffle a deck of cards.

At 1X, I saw rows of hands and forearms, denuded of housing and grasping toward the ceiling. Technicians seated along an assembly line were fastening artificial tendons to the fingers to link them with actuators in the wrist. Others attached electrical wire to sensors on the fingertips; the wire would eventually be routed to the robot’s brain. Nearby, a finger was being tested for durability. It pointed, curled back, then repeated the movements. A counter on a monitor noted that this action had been performed 2,860,631 times.

But here, again, the mechanical engineering was far ahead of the A.I. This point was confirmed during a demonstration at Skild, where I watched a Unitree robot carefully grab a white ceramic coffee cup from a table and set it upright in a bin. I moved the coffee cup back to the tabletop, and the robot’s eyelike cameras seemed to follow. Then I turned the cup on its side. The robot seemed perplexed. It moved its hand about six inches from the cup and began to grab uselessly in the air.

With a disapproving look, a technician set the cup upright, and the robot immediately returned it to the container. I took a blue plastic bowl from the bin and placed it upside down. The robot identified the object but couldn’t get a grip on it. As its hand pushed the bowl around fruitlessly, I gave a little smirk of human superiority. But then the robot stopped. And—I swear to this—it started to think. After about ten seconds, it perceived that the overturned bowl had a raised circular foot. Pinching the foot of the bowl, the robot picked it up and placed it in the bin. “See?” the technician said. “It figured it out.” ♦