post-1945 ruling elites, who were too incompetent or craven to use the country’s unrivalled wealth and power to advance their national interests. Worse, they embroiled America in forever wars in a naive belief that they could make the world a kindlier place. He maintained that tone of grievance throughout his first term. The second Trump presidency has seen grievance combined with talk of quasi-imperialist conquest. Upon returning to office in 2025, Mr Trump declared earlier presidents “stupid” for giving up American control of Greenland after the second world war, or for handing the Panama Canal to Panama, and pledged to take both back. This was not mere posturing. The tone was set in January after American troops snatched Venezuela’s leader from his home, allowing Mr Trump to hand-pick a more pliant ruler for that oil-rich country. “American dominance in the western hemisphere will never be questioned again,” he crowed. Now, in his sixth year as president, a third goal has joined grievance and dominance as a guiding principle of Mr Trump’s statecraft. That goal is vengeance. A desire for revenge helps explain Mr Trump’s fateful decision to join Israel in attacking Iran six months ago. “Regime Change”, a startlingly well-briefed book about the second Trump presidency by two White House correspondents, Maggie Haberman and Jonathan Swan, describes meetings in which Mr Trump savoured the chance to kill Iran’s top leaders and destroy their armed forces, whether or not this led to a better Iran. The Iranian regime had humiliated successive American presidents and tried to assassinate Mr Trump. Now he was being offered a chance to make them pay. A public aim of the war might have been the toppling of Iran’s despotic government. But the book describes Mr Trump, in a closed-door meeting with his close aides, dismissing Iranian regime change as “their problem”. Whether he meant the Iranian people’s problem or Israel’s, nobody quite knew. Punishment, though, was indisputably his intent. Now, as the Strait of Hormuz remains closed, much of Mr Trump’s wrath is aimed at allies and partners in Europe, Asia and the Arab world, whom he blames for failing to help him open that waterway. If victory remains elusive, expect Mr Trump to stay in revenge mode. The list of plausible targets is long. Members of the NATO alliance, notably Canada and
Denmark, Ukraine, South Korea and Cuba have all angered Mr Trump over the years. Big beasts such as Mr Xi have less to fear. Mr Trump, who sees himself as an alpha male to his core, was never likely to limp quietly from office. Now that his dominance is threatened, the world will find him more disruptive than ever. ■ This article was downloaded by zlibrary from https://www.economist.com/international/2026/08/25/as-his-presidency-flounders- trump-is-more-dangerous-than-ever
China is training up thousands of humanoid robots How Shein came crashing down The quality you should most wish for your children Americans should rekindle their love for big business Meta settles its blockbuster trial for up to $17bn One thing America still excels at making? Pretzels An obituary for the Drexel generation
China is training up thousands of humanoid robots But its approach will come with enormous costs Aug 27th 2026 China’s humanoid robots are sprinting ahead of their rivals—literally. On August 17th one of their number, called Superman, clocked up a running speed of 12.66 metres per second, beating the previous record set by Usain Bolt, before crashing into a wall. The triumph only added to the buzz over Unitree, Superman’s maker, which debuted its shares in Shanghai two days later. Their price leapt by 460%. Yet as the ignominious end of Superman’s running feat demonstrates, the technology still has a long way to go. Chinese companies are expected to sell 50,000 humanoids this year, more than triple last year’s figure. They
have largely mastered the hardware behind the machines. The software, however, is another matter. In order to create the foundation models that will allow robots to seamlessly carry out a multitude of useful tasks, enormous amounts of data must now be collected. The models powering the current generation of humanoids possess a few billion “parameters”; to replicate the functioning of the human body, they will need hundreds of billions. That would put them at a similar size to the large language models powering chatbots. The difference is that chatbots can be trained on the reams of digital text available on the internet. Gathering the data necessary to teach a robot to identify a glass, pick it up and fill it with coffee is much harder. The bot must understand everything from its spatial position to the brittleness of the glass and the viscosity of its contents. That information must be mined from experiences in the real world, or detailed recreations of them. Humanoids are currently fed a hotchpotch of data, often from low-quality simulations. Data collected from the real world are far more useful—and now highly sought after. The most valuable form is “real machine” data, which are generated by the actions of a robot, either when it is controlled remotely or when it is carrying out tasks by itself. Another important source comes from recording humans as they complete tasks. Known as “egocentric” data, this information is gathered by equipping a person with a headset, haptic-sensor gloves and other kit that records their movements. China is quickly becoming the frontrunner in the quest for real machine data, thanks to training centres such as the Hubei Humanoid Innovation Centre. At the sprawling facility in the central Chinese city of Wuhan, up to 100 robots spend hours each day observing and mimicking humans. At one of the dozens of work stations, a young man behind a counter is moving his hand, gloved in digital sensors, in a circular motion as if he were pouring hot water over coffee. Next to him stands a robot that is mimicking his motion but spouting real water from a kettle over a funnel of coffee. The manner in which the bot’s wrist and fingers move are creepily human. A few steps from the makeshift café is what looks like a pharmacy, where another human-robot duo are stocking shelves. Next is a convenience store, then a
factory line, followed by various other scenes from working life. (Until now foreign journalists have not been allowed to visit these centres.) The centre in Wuhan is one of 53 facilities in China built especially for gleaning the secrets of human movement, according to data from Interact Analysis, a consulting firm. Most were created in the past two years. Another 34 are under construction or planned. One being constructed in Shanghai will have space for 1,000 humanoids. A small city in coastal Zhejiang province already has six training centres. Training centres require a large amount of space and many people to run them, as well as a legion of cutting-edge humanoids, which can run to 100,000 yuan ($15,000) apiece. And for every eight hours of coffee-pouring, for example, the droid at the café station produces just three hours of useful data. The rest is spoiled, mostly by errors that engineers do not want the bots to learn. This form of training thus costs 500-700 yuan per hour, reckons Corey Chan of HSBC, a bank. According to one estimate, 100m training hours will be required to develop a robot that can perform a wide variety of daily tasks. Fortunately for Chinese businesses like Unitree, the government has been picking up much of the tab for the centres. Around four-fifths are state- backed. Many are collaborations between private enterprises and local governments, which buy humanoids and sell the data produced back to the companies. Estimates vary but in the first half of 2026 up to 70% of the humanoids made in China may have gone to these training centres, adding up to around 13,000 machines. By building one, local officials can shore up demand for robots that are being manufactured in their area. At the same time Chinese robot-makers are finding ways of collecting egocentric data from the country’s large manufacturing workforce—as well as its many unemployed youngsters. A cottage industry has emerged of vendors making wearable gear for that purpose. Some hope young people will wear the kit while at home as a part-time job. JD.com, an e-commerce firm, said earlier this year that it has launched a project to pay 100,000 of its staff and 500,000 others to track their own movements. At a facility that has reportedly received state funding in Jiangsu, another coastal province, the firm pays people to carry out tasks in fake grocery stores and other
environments. Over the next two years it intends to gather 10m hours of data capturing real-world human scenarios. Egocentric data generated by humans are far less useful than real machine data, owing to the differences in how human limbs and robotic ones move in practice. And even the bits that are useful must be labelled, requiring a human to tag each movement manually so that a bot knows to which limb or action it applies. Still, China gained an early edge in image-recognition technology by employing large groups of people to tag pictures. It could do the same again, says an engineer who works for a robotics company. China’s humanoid industry is unlike most other manufacturing businesses that have thrived in the country. Over the next few years it is set to produce and sell hundreds of thousands of costly but mostly useless machines in the hope that it can make cheap and useful ones in future. Since its initial pop, Unitree’s share price has slumped by 30%. American competitors have been relying on less expensive training methods. Tesla, America’s biggest producer of humanoids, is said to be training robots in its own warehouses, which saves it the cost of constructing standalone training facilities. Various companies have been using videos of human movement to train their humanoids. And since these days America has few factory workers who can be handed gear for egocentric collection, a number of firms are reportedly paying workers in poor countries where wages are lower than in China to don headsets and haptic gloves as they work.
As with computer vision, China nevertheless seems almost certain to maintain the lead in robot data collection. But at what cost? Given the current state of the technology, and the time that will be required to improve it, a commercial market for humanoids is unlikely to emerge this decade. Morgan Stanley, a bank, reckons that China could be selling nearly 450,000 robots a year by 2030 (see chart). Many will remain dim-witted—and continue charging into walls. ■ This article was downloaded by zlibrary from https://www.economist.com/business/2026/08/23/china-is-training-up-thousands-of- humanoid-robots