China is on monitor to dominate client synthetic intelligence functions and robotics manufacturing inside years, however the USA will keep its substantial lead in enterprise AI adoption and cutting-edge analysis, in accordance with Kai-Fu Lee, one of many world's most outstanding AI scientists and traders.
In a uncommon, unvarnished evaluation delivered through video hyperlink from Beijing to the TED AI convention in San Francisco Tuesday, Lee — a former govt at Apple, Microsoft, and Google who now runs each a serious enterprise capital agency and his personal AI firm — laid out a expertise panorama splitting alongside geographic and financial strains, with profound implications for each business competitors and nationwide safety.
"China's robotics has the benefit of getting built-in AI into a lot decrease prices, higher provide chain and quick turnaround, so corporations like Unitree are literally the farthest forward on the earth by way of constructing inexpensive, embodied humanoid AI," Lee stated, referring to a Chinese language robotics producer that has undercut Western rivals on value whereas advancing capabilities.
The feedback, made to a room stuffed with Silicon Valley executives, traders, and researchers, represented one of the detailed public assessments from Lee concerning the comparative strengths and weaknesses of the world's two AI superpowers — and urged that the race for synthetic intelligence management is changing into much less a single contest than a sequence of parallel competitions with completely different winners.
Why enterprise capital is flowing in reverse instructions within the U.S. and China
On the coronary heart of Lee's evaluation lies a basic distinction in how capital flows within the two international locations' innovation ecosystems. American enterprise capitalists, Lee stated, are pouring cash into generative AI corporations constructing giant language fashions and enterprise software program, whereas Chinese language traders are betting closely on robotics and {hardware}.
"The VCs within the US don't fund robotics the way in which the VCs do in China," Lee stated. "Similar to the VCs in China don't fund generative AI the way in which the VCs do within the US."
This funding divergence displays completely different financial incentives and market constructions. In the USA, the place corporations have grown accustomed to paying for software program subscriptions and the place labor prices are excessive, enterprise AI instruments that enhance white-collar productiveness command premium costs. In China, the place software program subscription fashions have traditionally struggled to realize traction however manufacturing dominates the economic system, robotics provides a clearer path to commercialization.
The end result, Lee urged, is that every nation is pulling forward in numerous domains — and should proceed to take action.
"China's received some challenges to beat in getting an organization funded in addition to OpenAI or Anthropic," Lee acknowledged, referring to the main American AI labs. "However I feel U.S., on the flip aspect, could have bother creating the funding curiosity and worth creation within the robotics" sector.
Why American corporations dominate enterprise AI whereas Chinese language corporations wrestle with subscriptions
Lee was specific about one space the place the USA maintains what seems to be a sturdy benefit: getting companies to truly undertake and pay for AI software program.
"The enterprise adoption will clearly be led by the USA," Lee stated. "The Chinese language corporations haven’t but developed a behavior of paying for software program on a subscription."
This seemingly mundane distinction in enterprise tradition — whether or not corporations pays month-to-month charges for software program — has grow to be a vital issue within the AI race. The explosion of spending on instruments like GitHub Copilot, ChatGPT Enterprise, and different AI-powered productiveness software program has fueled American corporations' skill to take a position billions in additional analysis and improvement.
Lee famous that China has traditionally overcome related challenges in client expertise by creating various enterprise fashions. "Within the early days of web software program, China was additionally properly behind as a result of individuals weren't prepared to pay for software program," he stated. "However then promoting fashions, e-commerce fashions actually propelled China ahead."
Nonetheless, he urged, somebody might want to "discover a new enterprise mannequin that isn't simply pay per software program per use or per thirty days foundation. That's going to not occur in China anytime quickly."
The implication: American corporations constructing enterprise AI instruments have a window — maybe a considerable one — the place they’ll generate income and reinvest in R&D with out dealing with severe Chinese language competitors of their core market.
How ByteDance, Alibaba and Tencent will outpace Meta and Google in client AI
The place Lee sees China pulling forward decisively is in consumer-facing AI functions — the type embedded in social media, e-commerce, and leisure platforms that billions of individuals use day by day.
"When it comes to client utilization, that's prone to occur," Lee stated, referring to China matching or surpassing the USA in AI deployment. "The Chinese language giants, like ByteDance and Alibaba and Tencent, will certainly transfer quite a bit quicker than their equal in the USA, corporations like Meta, YouTube and so forth."
Lee pointed to a cultural benefit: Chinese language expertise corporations have spent the previous decade obsessively optimizing for consumer engagement and product-market slot in brutally aggressive markets. "The Chinese language giants actually work tenaciously, and so they have mastered the artwork of determining product market match," he stated. "Now they’ve so as to add expertise to it. So that’s inevitably going to occur."
This evaluation aligns with current business observations. ByteDance's TikTok turned the world's most downloaded app by way of subtle AI-driven content material suggestion, and Chinese language corporations have pioneered AI-powered options in areas like live-streaming commerce and short-form video that Western corporations later copied.
Lee additionally famous that China has already deployed AI extra extensively in sure domains. "There are a variety of areas the place China has additionally performed an ideal job, corresponding to utilizing laptop imaginative and prescient, speech recognition, and translation extra extensively," he stated.
The shocking open-source shift that has Chinese language fashions beating Meta's Llama
Maybe Lee's most placing knowledge level involved open-source AI improvement — an space the place China seems to have seized management from American corporations in a remarkably quick time.
"The ten highest rated open supply [models] are from China," Lee stated. "These corporations have now eclipsed Meta's Llama, which was primary."
This represents a big shift. Meta's Llama fashions had been extensively seen because the gold customary for open-source giant language fashions as just lately as early 2024. However Chinese language corporations — together with Lee's personal agency, 01.AI, together with Alibaba, Baidu, and others — have launched a flood of open-source fashions that, in accordance with varied benchmarks, now outperform their American counterparts.
The open-source query has grow to be a flashpoint in AI improvement. Lee made an in depth case for why open-source fashions will show important to the expertise's future, whilst closed fashions from corporations like OpenAI command greater costs and, typically, superior efficiency.
"I feel open supply has a lot of main benefits," Lee argued. With open-source fashions, "you’ll be able to study it, tune it, enhance it. It's yours, and it's free, and it's essential for constructing if you wish to construct an software or tune the mannequin to do one thing particular."
He drew an analogy to working programs: "Individuals who work in working programs beloved Linux, and that's why its adoption went by way of the roof. And I feel sooner or later, open supply may even permit individuals to tune a sovereign mannequin for a rustic, make it work higher for a selected language."
Nonetheless, Lee predicted each approaches will coexist. "I don't suppose open supply fashions will win," he stated. "I feel similar to we now have Apple, which is closed, however supplies a considerably higher expertise than Android… I feel we're going to see extra apps utilizing open-source fashions, extra engineers wanting to construct open-source fashions, however I feel more cash will stay within the closed mannequin."
Why China's manufacturing benefit makes the robotics race 'not over, however' almost determined
On robotics, Lee's message was blunt: the mix of China's manufacturing prowess, decrease prices, and aggressive funding has created a bonus that can be tough for American corporations to beat.
When requested straight whether or not the robotics race was already over with China victorious, Lee hedged solely barely. "It's not over, however I feel the U.S. remains to be able to arising with the perfect robotic analysis concepts," he stated. "However the VCs within the U.S. don't fund robotics the way in which the VCs do in China."
The problem is structural. Constructing robots requires not simply software program and AI, however {hardware} manufacturing at scale — exactly the type of built-in provide chain and low-cost manufacturing that China has spent many years perfecting. Whereas American labs at universities and corporations like Boston Dynamics proceed to provide spectacular analysis prototypes, turning these prototypes into inexpensive business merchandise requires the manufacturing ecosystem that China possesses.
Corporations like Unitree have demonstrated this benefit concretely. The corporate's humanoid robots and quadrupedal robots value a fraction of their American-made equivalents whereas providing comparable or superior capabilities — a price-to-performance ratio that might show decisive in business markets.
The power infrastructure hole that might decide AI supremacy
Underlying many of those aggressive dynamics is an element Lee raised early in his remarks: power infrastructure. "China is now constructing new power initiatives at 10 instances the speed of the U.S.," he stated, "and if this continues, it can inevitably result in China having 10 instances the AI functionality of the U.S., whether or not we prefer it or not."
This commentary connects to a theme raised by a number of audio system on the TED AI convention: that computing energy — and the power to run it — has grow to be the basic constraint on AI improvement. If China can construct energy crops and knowledge facilities at 10 instances the speed of the USA, it may merely outspend American rivals in coaching ever-larger fashions and operating them at ever-greater scale.
Lee famous this dynamic carries "very actual nationwide safety implications for the U.S." — although he didn’t elaborate on what these implications is perhaps. The remark appeared to reference rising issues in Washington about technological competitors with China, notably in areas like AI-enabled army programs, surveillance capabilities, and financial competitiveness.
Regardless of the USA at the moment internet hosting a number of instances extra AI computing energy than China, Lee warned that "this lead is rising" for now however may reverse if power infrastructure investments proceed at present charges.
What worries Lee most: not AGI, however the race itself
Regardless of his typically measured tone about China's AI improvement, Lee expressed concern about one space the place he believes the worldwide AI group faces actual hazard — not the far-future threat of superintelligent AI, however the near-term penalties of transferring too quick.
When requested about AGI dangers, Lee reframed the query. "I'm much less afraid of AI changing into self-aware and inflicting hazard for people within the quick time period," he stated, "however extra anxious about it being utilized by unhealthy individuals to do horrible issues, or by the AI race pushing individuals to work so exhausting, so quick and livid and transfer quick and break issues that they construct merchandise which have issues and holes to be exploited."
He continued: "I'm very anxious about that. Actually, I feel some horrible occasion will occur that can be a get up name from this kind of drawback."
Lee's perspective carries uncommon weight due to his distinctive vantage level spanning each Chinese language and American AI improvement. Over a profession spanning greater than three many years, he has held senior positions at Apple, Microsoft, and Google, whereas additionally founding Sinovation Ventures, which has invested in additional than 400 corporations throughout each international locations. His AI firm, 01.AI, based in 2023, has launched a number of open-source fashions that rank among the many most succesful on the earth.
For American corporations and policymakers, Lee's evaluation presents a fancy strategic image. The USA seems to have clear benefits in enterprise AI software program, basic analysis, and computing infrastructure. However China is transferring quicker in client functions, manufacturing robotics at decrease prices, and probably pulling forward in open-source mannequin improvement.
The bifurcation means that relatively than a single "winner" in AI, the world could also be heading towards a expertise panorama the place completely different international locations excel in numerous domains — with all of the financial and geopolitical issues that suggests.
Because the TED AI convention continued Wednesday, Lee's evaluation hung over subsequent discussions. His message appeared clear: the AI race shouldn’t be one contest, however many — and the USA and China are every profitable completely different races.
Standing within the convention corridor afterward, one enterprise capitalist, who requested to not be named, summed up the temper within the room: "We're not competing with China anymore. We're competing on parallel tracks." Whether or not these tracks finally converge — or diverge into fully separate expertise ecosystems — would be the defining query of the following decade.
