robotics as the key to unlocking China\u2019s future economic potential<\/a> as it grapples with an ageing and shrinking workforce. Marketing materials for robotic companies show their products performing all kinds of tasks that humans will supposedly soon be free of: folding laundry, cooking, cutting hair.<\/p>\nA humanoid robot wearing a traditional mamianqun skirt strikes a Chinese drum at the Linkerbot office in May in Beijing. Photograph: Emmanuel Wong\/The Guardian<\/p>\n
Beijing has repeatedly emphasised the importance of \u201cembodied AI\u201d in China\u2019s development plans. In May, the Chinese Communist party\u2019s theoretical journal, Qiushi, published a report that said \u201cembodied-intelligence robots\u201d were among the sectors \u201copening up new trillion-yuan markets\u201d.<\/p>\n
But although China is racing ahead in the deployment of automatons \u2013 more than half of the factory robots that are installed each year are in China \u2013 the use cases for humanoids remain minimal. \u201cTrue multipurpose humanoids are far off yet,\u201d concluded the International Federation of Robotics in a report published last September.<\/p>\n
That is because many of the tasks that would make humanoids useful in daily settings require human-like hands. And making them is extremely difficult. Last year, Elon Musk, whose company Tesla makes the Optimus humanoid, said hands represented the \u201cmajority of the engineering difficulty of the entire robot\u201d.<\/p>\n
\u2018100 times more difficult\u2019<\/p>\n
In an office brimming with writhing, floating robotic hands of various weights and sizes, the founder of LinkerBot, one of China\u2019s leading dextrous hands companies, explains the challenge.<\/p>\n
Making a robotic hand is \u201cone hundred times more difficult\u201d than making a humanoid, Zhou Yong says. \u201cIts dexterity is 10 times that of other body parts. But its volume is only one tenth of other body parts\u201d.<\/p>\n
Alex Zhou, founder of tech startup Linkerbot, poses for a photo alongside a humanoid robot and a robotic dextrous hand at the company\u2019s office in May in Beijing. Photograph: Emmanuel Wong\/The Guardian<\/p>\n
Like many Chinese entrepreneurs, Zhou is inspired by the American greats. Having graduated from Huazhong University of Science and Technology, one of China\u2019s top schools, Zhou was interested in designing apps as well as robotics. But he listened to the quote from Steve Jobs about the importance of focus (\u201cInnovation is saying no to 1,000 things\u201d) and decided to focus just on hands, launching LinkerBot in 2023. The company now makes about 5,000 hands a month and has plans to double that figure as it chases a valuation of $6bn. \u201cHuman hands are the most important ability of human beings,\u201d Zhou says. \u201cIf we focus on this one point, it is easier to realise many human skills.\u201d<\/p>\n
Among Zhou\u2019s ambitions are to make mass-market prosthetic hands for amputees at a fraction of the current price, which can be tens of thousands of dollars. Zhou believes his company will be able to bring the price down to just $1,000 per hand.<\/p>\n
Making robotic hands requires solving hardware and software problems.<\/p>\n
A technician calibrates a robotic dextrous hand mounted on a mechanical arm at Linkerbot. Photograph: Emmanuel Wong\/The Guardian<\/p>\n
Thanks to a cheap, sophisticated and nimble manufacturing supply chain, Chinese companies are racing ahead on the hardware side. The rise of China\u2019s electric vehicle industry has produced many companies that are capable of producing the components needs for robots at scale, from lithium-ion batteries to miniaturised motors.<\/p>\n
Pan Yunzhe, the founder of Wuji Technology, a Shenzhen-based robotic hands company, says the ease of sourcing components in China is the reason he founded his company there rather than in the US, where he graduated in 2018.<\/p>\n
![\"Humanoid](\"https:\/\/www.newsbeep.com\/us\/wp-content\/uploads\/2026\/07\/Humanoid_robots_playing_music_--6490dce4-73dc-4344-b09a-062d989bf35b-1.0.0000000.jpg\")
Humanoid robots playing music<\/p>\n
\u201cIt was really impossible to do hardware in the United States because the supply chain problem is just so constraining,\u201d he says. When he tried to start a company in the US, he needed to ask his father to post parts to him. So he decided to return to China to start his company there instead.<\/p>\n
Teaching hands to move<\/p>\n
Zhou and Pan are two of the thousands of entrepreneurs betting on China\u2019s robotics hype. China has now registered more than 1m robotic companies, with registrations in 2025 up 40% on the previous year. The companies focused only on hands represent a fraction of that market, but it is growing fast. Last year the dextrous hand industry in China surpassed 50bn yuan ($7.4bn), according to Chinese media, up from 13bn yuan in 2024.<\/p>\n
Pan says he decided to focus on hands because \u201cthe problem of manipulation is much more important than the problem of locomotion\u201d. Humanoids can move through space, but until they can manipulate tools, they are all but useless.<\/p>\n
The more challenging problem is software \u2013 how to teach the hands how to do things.<\/p>\n
\u201cThe challenge of making these hands is getting solved now,\u201d says Nathan Lepora, a professor of robotics and AI at the University of Bristol. \u201cControlling them, now that\u2019s a whole different game \u2026 nobody knows how to do that.\u201d<\/p>\n
A technician demonstrates teleoperation controls on a humanoid robot. Photograph: Emmanuel Wong\/The Guardian<\/p>\n
Anyone who has tried to operate a claw machine at a funfair to grab a stuffed toy knows how difficult it is to control a machine from afar \u2013 a process known as teleoperation.<\/p>\n
But that is exactly what many start-ups are trying to do at scale to harvest the vast amounts of data needed to train spatial intelligence models. Unlike large language models, which can be trained on the virtually infinite reams of text available on the internet, data sources for three-dimensional models are scarce.<\/p>\n
As well as teleoperating robotic hands, which can require hundreds of training hours to teach a robot to do a task as simple as packing a bag of groceries, researchers are increasingly moving towards more seamless methods, such as getting humans to wear sensors that can collect data as the human goes about their daily life.<\/p>\n
One of Wuji\u2019s flagship products is the Wuji glove, a sensor-filled wearable device that can collect movement data as well as more subtle but vital information about pressure and touch. That kind of information is intuitive to humans and allows someone to crack an egg on the edge of a frying pan rather than crush it with their bare hands, skills that are still alien territory for robots.<\/p>\n
\u201cThe two most fundamental problems in dextrous manipulation in terms of data collection are capturing how a human moves and what humans are touching or feeling,\u201d says Pan. Those questions are \u201csuper complicated and not solved yet\u201d.<\/p>\n
But China\u2019s entrepreneurs are betting they will be the ones to solve it. LinkerBot\u2019s Zhou dreams of a future where a factory of robotic hands builds more robotic hands \u2013 a self-perpetuating loop that has minimal human input. Further down the line, with the right hands, robots might be able to become fully-fledged household helpers.<\/p>\n
\u201cWe are not creating robots to replace labour,\u201d Zhou says. \u201cWe are creating robots so that humans can live a better and more prosperous life.\u201d<\/p>\n
Additional research by Lillian Yang and Yu-chen Li<\/p>\n","protected":false},"excerpt":{"rendered":"Human hands \u2013 nimble, nerve-filled appendages that are the most flexible part of the human skeleton \u2013 are…\n","protected":false},"author":2,"featured_media":745652,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[45],"tags":[182,181,507,74],"class_list":["post-745651","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/745651","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/comments?post=745651"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/posts\/745651\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media\/745652"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/media?parent=745651"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/categories?post=745651"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us\/wp-json\/wp\/v2\/tags?post=745651"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}