China is on observe to dominate client synthetic intelligence purposes and robotics manufacturing inside years, however the US will keep its substantial lead in enterprise AI adoption and cutting-edge analysis, based on Kai-Fu Lee, one of many world's most distinguished AI scientists and buyers.
In a uncommon, unvarnished evaluation delivered by way of video hyperlink from Beijing to the TED AI convention in San Francisco Tuesday, Lee — a former government at Apple, Microsoft, and Google who now runs each a significant enterprise capital agency and his personal AI firm — laid out a expertise panorama splitting alongside geographic and financial traces, with profound implications for each industrial competitors and nationwide safety.
"China's robotics has the advantage of having integrated AI into much lower costs, better supply chain and fast turnaround, so companies like Unitree are actually the farthest ahead in the world in terms of building affordable, embodied humanoid AI," Lee mentioned, referring to a Chinese language robotics producer that has undercut Western opponents on value whereas advancing capabilities.
The feedback, made to a room crammed with Silicon Valley executives, buyers, and researchers, represented one of the vital detailed public assessments from Lee concerning the comparative strengths and weaknesses of the world's two AI superpowers — and recommended that the race for synthetic intelligence management is turning 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 nations' innovation ecosystems. American enterprise capitalists, Lee mentioned, are pouring cash into generative AI firms constructing giant language fashions and enterprise software program, whereas Chinese language buyers are betting closely on robotics and {hardware}.
"The VCs in the US don't fund robotics the way the VCs do in China," Lee mentioned. "Just like the VCs in China don't fund generative AI the way the VCs do in the US."
This funding divergence displays completely different financial incentives and market constructions. In the US, the place firms 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 financial system, robotics affords a clearer path to commercialization.
The end result, Lee recommended, is that every nation is pulling forward in numerous domains — and will proceed to take action.
"China's got some challenges to overcome in getting a company funded as well as OpenAI or Anthropic," Lee acknowledged, referring to the main American AI labs. "But I think U.S., on the flip side, will have trouble developing the investment interest and value creation in the robotics" sector.
Why American firms dominate enterprise AI whereas Chinese language corporations wrestle with subscriptions
Lee was specific about one space the place the US maintains what seems to be a sturdy benefit: getting companies to really undertake and pay for AI software program.
"The enterprise adoption will clearly be led by the United States," Lee mentioned. "The Chinese companies have not yet developed a habit of paying for software on a subscription."
This seemingly mundane distinction in enterprise tradition — whether or not firms can pay month-to-month charges for software program — has turn into 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 firms' capacity to take a position billions in additional analysis and growth.
Lee famous that China has traditionally overcome comparable challenges in client expertise by creating various enterprise fashions. "In the early days of internet software, China was also well behind because people weren't willing to pay for software," he mentioned. "But then advertising models, e-commerce models really propelled China forward."
Nonetheless, he recommended, somebody might want to "find a new business model that isn't just pay per software per use or per month basis. That's going to not happen in China anytime soon."
The implication: American firms constructing enterprise AI instruments have a window — maybe a considerable one — the place they’ll generate income and reinvest in R&D with out going through 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 purposes — the sort embedded in social media, e-commerce, and leisure platforms that billions of individuals use each day.
"In terms of consumer usage, that's likely to happen," Lee mentioned, referring to China matching or surpassing the US in AI deployment. "The Chinese giants, like ByteDance and Alibaba and Tencent, will definitely move a lot faster than their equivalent in the United States, companies like Meta, YouTube and so on."
Lee pointed to a cultural benefit: Chinese language expertise firms have spent the previous decade obsessively optimizing for consumer engagement and product-market slot in brutally aggressive markets. "The Chinese giants really work tenaciously, and they have mastered the art of figuring out product market fit," he mentioned. "Now they have to add technology to it. So that is inevitably going to happen."
This evaluation aligns with current business observations. ByteDance's TikTok grew to become the world's most downloaded app via subtle AI-driven content material advice, and Chinese language firms have pioneered AI-powered options in areas like live-streaming commerce and short-form video that Western firms later copied.
Lee additionally famous that China has already deployed AI extra extensively in sure domains. "There are a lot of areas where China has also done a great job, such as using computer vision, speech recognition, and translation more widely," he mentioned.
The stunning open-source shift that has Chinese language fashions beating Meta's Llama
Maybe Lee's most putting knowledge level involved open-source AI growth — an space the place China seems to have seized management from American firms in a remarkably quick time.
"The 10 highest rated open source [models] are from China," Lee mentioned. "These companies have now eclipsed Meta's Llama, which used to be number one."
This represents a big shift. Meta's Llama fashions have been extensively considered because the gold customary for open-source giant language fashions as not too long ago as early 2024. However Chinese language firms — together with Lee's personal agency, 01.AI, together with Alibaba, Baidu, and others — have launched a flood of open-source fashions that, based on varied benchmarks, now outperform their American counterparts.
The open-source query has turn into a flashpoint in AI growth. Lee made an in depth case for why open-source fashions will show important to the expertise's future, at the same time as closed fashions from firms like OpenAI command greater costs and, usually, superior efficiency.
"I think open source has a number of major advantages," Lee argued. With open-source fashions, "you can examine it, tune it, improve it. It's yours, and it's free, and it's important for building if you want to build an application or tune the model to do something specific."
He drew an analogy to working techniques: "People who work in operating systems loved Linux, and that's why its adoption went through the roof. And I think in the future, open source will also allow people to tune a sovereign model for a country, make it work better for a particular language."
Nonetheless, Lee predicted each approaches will coexist. "I don't think open source models will win," he mentioned. "I think just like we have Apple, which is closed, but provides a somewhat better experience than Android… I think we're going to see more apps using open-source models, more engineers wanting to build open-source models, but I think more money will remain in the closed model."
Why China's manufacturing benefit makes the robotics race 'not over, however' almost determined
On robotics, Lee's message was blunt: the mixture of China's manufacturing prowess, decrease prices, and aggressive funding has created a bonus that will probably be troublesome for American firms to beat.
When requested immediately whether or not the robotics race was already over with China victorious, Lee hedged solely barely. "It's not over, but I think the U.S. is still capable of coming up with the best robotic research ideas," he mentioned. "But the VCs in the U.S. don't fund robotics the way 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 sort of built-in provide chain and low-cost manufacturing that China has spent many years perfecting. Whereas American labs at universities and firms like Boston Dynamics proceed to provide spectacular analysis prototypes, turning these prototypes into reasonably priced industrial merchandise requires the manufacturing ecosystem that China possesses.
Firms like Unitree have demonstrated this benefit concretely. The corporate's humanoid robots and quadrupedal robots price a fraction of their American-made equivalents whereas providing comparable or superior capabilities — a price-to-performance ratio that might show decisive in industrial markets.
The vitality infrastructure hole that might decide AI supremacy
Underlying many of those aggressive dynamics is an element Lee raised early in his remarks: vitality infrastructure. "China is now building new energy projects at 10 times the rate of the U.S.," he mentioned, "and if this continues, it will inevitably lead to China having 10 times the AI capability of the U.S., whether we like it or not."
This statement connects to a theme raised by a number of audio system on the TED AI convention: that computing energy — and the vitality to run it — has turn into the basic constraint on AI growth. If China can construct energy crops and knowledge facilities at 10 occasions the speed of the US, it might merely outspend American opponents in coaching ever-larger fashions and working them at ever-greater scale.
Lee famous this dynamic carries "very real national security implications for the U.S." — although he didn’t elaborate on what these implications could be. The remark appeared to reference rising issues in Washington about technological competitors with China, significantly in areas like AI-enabled army techniques, surveillance capabilities, and financial competitiveness.
Regardless of the US presently internet hosting a number of occasions extra AI computing energy than China, Lee warned that "this lead is growing" for now however might reverse if vitality 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 growth, Lee expressed concern about one space the place he believes the worldwide AI neighborhood faces actual hazard — not the far-future danger of superintelligent AI, however the near-term penalties of transferring too quick.
When requested about AGI dangers, Lee reframed the query. "I'm less afraid of AI becoming self-aware and causing danger for humans in the short term," he mentioned, "but more worried about it being used by bad people to do terrible things, or by the AI race pushing people to work so hard, so fast and furious and move fast and break things that they build products that have problems and holes to be exploited."
He continued: "I'm very worried about that. In fact, I think some terrible event will happen that will be a wake up call from this sort of problem."
Lee's perspective carries uncommon weight due to his distinctive vantage level spanning each Chinese language and American AI growth. 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 firms throughout each nations. 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 firms and policymakers, Lee's evaluation presents a posh 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 purposes, manufacturing robotics at decrease prices, and doubtlessly pulling forward in open-source mannequin growth.
The bifurcation means that fairly than a single "winner" in AI, the world could also be heading towards a expertise panorama the place completely different nations excel in numerous domains — with all of the financial and geopolitical issues that means.
Because the TED AI convention continued Wednesday, Lee's evaluation hung over subsequent discussions. His message appeared clear: the AI race just isn’t one contest, however many — and the US 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 totally separate expertise ecosystems — could be the defining query of the subsequent decade.
