China is on track to dominate consumer artificial intelligence applications and robotics manufacturing within years, but the United States will maintain its substantial lead in enterprise AI adoption and cutting-edge research, according to <a href="https://en.wikipedia.org/wiki/Kai-Fu_Lee">Kai-Fu Lee</a>, one of the world&#x27;s most prominent AI scientists and investors.In a rare, unvarnished assessment delivered via video link from Beijing to the <a href="https://tedai-sanfrancisco.ted.com/">TED AI conference</a> in San Francisco Tuesday, Lee — a former executive at Apple, Microsoft, and Google who now runs both a major venture capital firm and his own AI company — laid out a technology landscape splitting along geographic and economic lines, with profound implications for both commercial competition and national security.&quot;China&#x27;s robotics has the advantage of having integrated AI into much lower costs, better supply chain and fast turnaround, so companies like <a href="https://www.unitree.com/">Unitree</a> are actually the farthest ahead in the world in terms of building affordable, embodied humanoid AI,&quot; Lee said, referring to a Chinese robotics manufacturer that has undercut Western competitors on price while advancing capabilities.The comments, made to a room filled with Silicon Valley executives, investors, and researchers, represented one of the most detailed public assessments from Lee about the comparative strengths and weaknesses of the world&#x27;s two AI superpowers — and suggested that the race for artificial intelligence leadership is becoming less a single contest than a series of parallel competitions with different winners.<h2>Why venture capital is flowing in opposite directions in the U.S. and China</h2>At the heart of Lee&#x27;s analysis lies a fundamental difference in how capital flows in the two countries&#x27; innovation ecosystems. American venture capitalists, Lee said, are pouring money into generative AI companies building large language models and enterprise software, while Chinese investors are betting heavily on robotics and hardware.&quot;The VCs in the US don&#x27;t fund robotics the way the VCs do in China,&quot; Lee said. &quot;Just like the VCs in China don&#x27;t fund generative AI the way the VCs do in the US.&quot;This investment divergence reflects different economic incentives and market structures. In the United States, where companies have grown accustomed to paying for software subscriptions and where labor costs are high, enterprise AI tools that boost white-collar productivity command premium prices. In China, where software subscription models have historically struggled to gain traction but manufacturing dominates the economy, robotics offers a clearer path to commercialization.The result, Lee suggested, is that each country is pulling ahead in different domains — and may continue to do so.&quot;China&#x27;s got some challenges to overcome in getting a company funded as well as OpenAI or Anthropic,&quot; Lee acknowledged, referring to the leading American AI labs. &quot;But I think U.S., on the flip side, will have trouble developing the investment interest and value creation in the robotics&quot; sector.<h2>Why American companies dominate enterprise AI while Chinese firms struggle with subscriptions</h2>Lee was explicit about one area where the United States maintains what appears to be a durable advantage: getting businesses to actually adopt and pay for AI software.&quot;The enterprise adoption will clearly be led by the United States,&quot; Lee said. &quot;The Chinese companies have not yet developed a habit of paying for software on a subscription.&quot;This seemingly mundane difference in business culture — whether companies will pay monthly fees for software — has become a critical factor in the AI race. The explosion of spending on tools like <a href="https://github.com/features/copilot">GitHub Copilot</a>, <a href="https://chatgpt.com/business/enterprise?utm_source=google&amp;utm_medium=paidsearch_brand&amp;utm_campaign=GOOG_B_SEM_GBR_Core_ENT_BAU_ACQ_PER_BRD_ALL_NAMER_US_EN_080625&amp;utm_term=chatgpt%20enterprise&amp;utm_content=182507886919&amp;utm_ad=779434575256&amp;utm_match=b&amp;gad_source=1&amp;gad_campaignid=22855802308&amp;gbraid=0AAAAA-I0E5deWS9iAj-S2JPixEaUT67Un&amp;gclid=CjwKCAjwgeLHBhBuEiwAL5gNEQgjDKgZm5up9BDA-oZ1HLMAECMm5XlfJerkJ9BbJgtkYf9GcAAQUhoCrskQAvD_BwE">ChatGPT Enterprise</a>, and other AI-powered productivity software has fueled American companies&#x27; ability to invest billions in further research and development.Lee noted that China has historically overcome similar challenges in consumer technology by developing alternative business models. &quot;In the early days of internet software, China was also well behind because people weren&#x27;t willing to pay for software,&quot; he said. &quot;But then advertising models, e-commerce models really propelled China forward.&quot;Still, he suggested, someone will need to &quot;find a new business model that isn&#x27;t just pay per software per use or per month basis. That&#x27;s going to not happen in China anytime soon.&quot;The implication: American companies building enterprise AI tools have a window — perhaps a substantial one — where they can generate revenue and reinvest in R&amp;D without facing serious Chinese competition in their core market.<h2>How ByteDance, Alibaba and Tencent will outpace Meta and Google in consumer AI</h2>Where Lee sees China pulling ahead decisively is in consumer-facing AI applications — the kind embedded in social media, e-commerce, and entertainment platforms that billions of people use daily.&quot;In terms of consumer usage, that&#x27;s likely to happen,&quot; Lee said, referring to China matching or surpassing the United States in AI deployment. &quot;The Chinese giants, like <a href="https://www.bytedance.com/en/">ByteDance</a> and <a href="https://www.alibaba.com/">Alibaba</a> and <a href="https://www.tencent.com/">Tencent</a>, will definitely move a lot faster than their equivalent in the United States, companies like <a href="https://www.meta.com/">Meta</a>, <a href="https://www.youtube.com/">YouTube</a> and so on.&quot;Lee pointed to a cultural advantage: Chinese technology companies have spent the past decade obsessively optimizing for user engagement and product-market fit in brutally competitive markets. &quot;The Chinese giants really work tenaciously, and they have mastered the art of figuring out product market fit,&quot; he said. &quot;Now they have to add technology to it. So that is inevitably going to happen.&quot;This assessment aligns with recent industry observations. ByteDance&#x27;s <a href="https://www.tiktok.com/en/">TikTok</a> became the world&#x27;s most downloaded app through sophisticated AI-driven content recommendation, and Chinese companies have pioneered AI-powered features in areas like live-streaming commerce and short-form video that Western companies later copied.Lee also noted that China has already deployed AI more widely in certain domains. &quot;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,&quot; he said.<h2>The surprising open-source shift that has Chinese models beating Meta&#x27;s Llama</h2>Perhaps Lee&#x27;s most striking data point concerned <a href="https://venturebeat.com/ai/why-open-source-ai-became-an-american-national-priority">open-source AI development</a> — an area where China appears to have seized leadership from American companies in a remarkably short time.&quot;The 10 highest rated open source [models] are from China,&quot; Lee said. &quot;These companies have now eclipsed Meta&#x27;s Llama, which used to be number one.&quot;This represents a significant shift. Meta&#x27;s <a href="https://venturebeat.com/ai/metas-answer-to-deepseek-is-here-llama-4-launches-with-long-context-scout-and-maverick-models-and-2t-parameter-behemoth-on-the-way">Llama models</a> were widely viewed as the gold standard for open-source large language models as recently as early 2024. But Chinese companies — including Lee&#x27;s own firm, <a href="http://01.ai">01.AI</a>, along with <a href="https://www.alibaba.com/">Alibaba</a>, <a href="https://www.baidu.com/">Baidu</a>, and others — have released a flood of open-source models that, according to various benchmarks, now outperform their American counterparts.The open-source question has become a flashpoint in AI development. Lee made an extensive case for why open-source models will prove essential to the technology&#x27;s future, even as closed models from companies like OpenAI command higher prices and, often, superior performance.&quot;I think open source has a number of major advantages,&quot; Lee argued. With open-source models, &quot;you can examine it, tune it, improve it. It&#x27;s yours, and it&#x27;s free, and it&#x27;s important for building if you want to build an application or tune the model to do something specific.&quot;He drew an analogy to operating systems: &quot;People who work in operating systems loved Linux, and that&#x27;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.&quot;Still, Lee predicted both approaches will coexist. &quot;I don&#x27;t think open source models will win,&quot; he said. &quot;I think just like we have Apple, which is closed, but provides a somewhat better experience than Android... I think we&#x27;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.&quot;<h2>Why China&#x27;s manufacturing advantage makes the robotics race &#x27;not over, but&#x27; nearly decided</h2>On robotics, Lee&#x27;s message was blunt: the combination of China&#x27;s manufacturing prowess, lower costs, and aggressive investment has created an advantage that will be difficult for American companies to overcome.When asked directly whether the robotics race was already over with China victorious, Lee hedged only slightly. &quot;It&#x27;s not over, but I think the U.S. is still capable of coming up with the best robotic research ideas,&quot; he said. &quot;But the VCs in the U.S. don&#x27;t fund robotics the way the VCs do in China.&quot;The challenge is structural. Building robots requires not just software and AI, but hardware manufacturing at scale — precisely the kind of integrated supply chain and low-cost production that China has spent decades perfecting. While American labs at universities and companies like <a href="https://bostondynamics.com/">Boston Dynamics</a> continue to produce impressive research prototypes, turning those prototypes into affordable commercial products requires the manufacturing ecosystem that China possesses.Companies like <a href="https://www.unitree.com/">Unitree</a> have demonstrated this advantage concretely. The company&#x27;s humanoid robots and quadrupedal robots cost a fraction of their American-made equivalents while offering comparable or superior capabilities — a price-to-performance ratio that could prove decisive in commercial markets.<h2>What worries Lee most: not AGI, but the race itself</h2>Despite his generally measured tone about China&#x27;s AI development, Lee expressed concern about one area where he believes the global AI community faces real danger — not the far-future risk of superintelligent AI, but the near-term consequences of moving too fast.When asked about <a href="https://venturebeat.com/ai/study-warns-of-security-risks-as-os-agents-gain-control-of-computers-and-phones">AGI risks</a>, Lee reframed the question. &quot;I&#x27;m less afraid of AI becoming self-aware and causing danger for humans in the short term,&quot; he said, &quot;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.&quot;He continued: &quot;I&#x27;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.&quot;Lee&#x27;s perspective carries unusual weight because of his unique vantage point spanning both Chinese and American AI development. Over a career spanning more than three decades, he has held senior positions at <a href="https://www.apple.com/">Apple</a>, <a href="https://www.microsoft.com/en-us/">Microsoft</a>, and <a href="https://www.google.com/?zx=1761178473681&amp;no_sw_cr=1">Google</a>, while also founding <a href="https://www.sinovationventures.com/">Sinovation Ventures</a>, which has invested in more than 400 companies across both countries. His AI company, <a href="http://01.ai">01.AI</a>, founded in 2023, has released several <a href="https://huggingface.co/01-ai">open-source models</a> that rank among the most capable in the world.For American companies and policymakers, Lee&#x27;s analysis presents a complex strategic picture. The United States appears to have clear advantages in enterprise AI software, fundamental research, and computing infrastructure. But China is moving faster in consumer applications, manufacturing robotics at lower costs, and potentially pulling ahead in open-source model development.The bifurcation suggests that rather than a single &quot;winner&quot; in AI, the world may be heading toward a technology landscape where different countries excel in different domains — with all the economic and geopolitical complications that implies.As the <a href="https://tedai-sanfrancisco.ted.com/">TED AI conference</a> continued Wednesday, Lee&#x27;s assessment hung over subsequent discussions. His message seemed clear: the AI race is not one contest, but many — and the United States and China are each winning different races.Standing in the conference hall afterward, one venture capitalist, who asked not to be named, summed up the mood in the room: &quot;We&#x27;re not competing with China anymore. We&#x27;re competing on parallel tracks.&quot; Whether those tracks eventually converge — or diverge into entirely separate technology ecosystems — may be the defining question of the next decade.

قدم كاي-فو لي، أحد أبرز خبراء الذكاء الاصطناعي، تحذيرًا صارمًا بشأن مستقبل الذكاء الاصطناعي، حيث أشار إلى أن الصين على وشك التفوق على الولايات المتحدة في تطبيقات الذكاء الاصطناعي الاستهلاكية وتصنيع الروبوتات. بينما ستظل الولايات المتحدة متقدمة في الذكاء الاصطناعي المؤسسي والبحث المتقدم، فإن هذا التحول قد يكون له تداعيات كبيرة على الهيمنة التكنولوجية العالمية والقوة الاقتصادية. من الضروري فهم هذه الديناميكيات لأنها ستشكل المشهد التنافسي في التكنولوجيا والابتكار لسنوات قادمة.

Kai-Fu Lee, un destacado experto en IA, ha emitido una advertencia contundente sobre el futuro de la inteligencia artificial, afirmando que China está lista para superar a EE. UU. en aplicaciones de IA para consumidores y fabricación de robótica. Aunque EE. UU. mantendrá su liderazgo en IA empresarial y en investigación, este cambio podría tener implicaciones significativas para el dominio tecnológico global y el poder económico. Comprender estas dinámicas es crucial, ya que darán forma al panorama competitivo en tecnología e innovación en los próximos años.

Kai-Fu Lee, un expert en IA de premier plan, a lancé un avertissement sévère concernant l'avenir de l'intelligence artificielle, affirmant que la Chine est prête à dépasser les États-Unis dans le domaine de l'IA grand public et de la fabrication de robots. Bien que les États-Unis conservent leur avance dans l'IA d'entreprise et la recherche, ce changement pourrait avoir des implications significatives pour la domination technologique mondiale et le pouvoir économique. Comprendre ces dynamiques est crucial car elles façonneront le paysage concurrentiel de la technologie et de l'innovation pour les années à venir.

Kai-Fu Lee, a leading AI expert, has delivered a stark warning about the future of artificial intelligence, stating that China is poised to outpace the U.S. in consumer AI and robotics manufacturing. While the U.S. will still lead in enterprise AI and research, this shift could have significant implications for global tech dominance and economic power. Understanding these dynamics is crucial as they will shape the competitive landscape in technology and innovation for years to come.

Kai-Fu Lee's brutal assessment: America is already losing the AI hardware war to China

Anyone looking to bet against US stocks this month would be wise to consider the strength of the American economy and ongoing enthusiasm around artificial intelligence.

هذا الشهر، يُنصح المستثمرون الذين يفكرون في بيع الأسهم الأمريكية على المكشوف بإعادة النظر في موقفهم بسبب الأداء القوي للاقتصاد الأمريكي والحماس المستمر حول الذكاء الاصطناعي (AI)، كما أشار 22V. تشير مجموعة هذه العوامل إلى بيئة محتملة الخطورة للمراهنة ضد السوق.

Este mes, se aconseja a los inversores que consideren vender en corto acciones estadounidenses que reconsideren su posición debido al sólido rendimiento de la economía estadounidense y al entusiasmo en torno a la inteligencia artificial (IA), según 22V. La combinación de estos factores sugiere un entorno potencialmente arriesgado para apostar en contra del mercado.

Ce mois-ci, les investisseurs envisageant de vendre à découvert des actions américaines sont conseillés de reconsidérer leur position en raison de la solide performance de l'économie américaine et de l'enthousiasme croissant autour de l'intelligence artificielle (IA), comme l'indique 22V. La combinaison de ces facteurs suggère un environnement potentiellement risqué pour parier contre le marché.

This month, investors considering shorting US stocks are advised to reconsider due to the robust performance of the American economy and the prevailing excitement surrounding artificial intelligence (AI), as noted by 22V. The combination of these factors suggests a potentially risky environment for betting against the market.

Economy and AI Push Make Shorting US Stocks Dangerous, 22V Says

Apple's head of artificial intelligence and machine learning has stepped down from the company.&#160; [object Object]

استقال رئيس قسم الذكاء الاصطناعي وتعلم الآلة في شركة آبل، مما يمثل تحولًا كبيرًا في قيادة الشركة وسط مخاوف متزايدة بشأن موقعها في السوق التكنولوجي التنافسي.

El jefe de inteligencia artificial y aprendizaje automático de Apple ha renunciado, marcando un cambio significativo en el liderazgo de la empresa en medio de crecientes preocupaciones sobre su posición en el competitivo panorama tecnológico.

Le responsable de l'intelligence artificielle et de l'apprentissage automatique d'Apple a quitté son poste, marquant un changement significatif dans la direction de l'entreprise au milieu de préoccupations croissantes concernant sa position sur le marché technologique compétitif.

Apple's head of artificial intelligence and machine learning has stepped down, marking a significant shift in the company's leadership amid growing concerns about its position in the competitive tech landscape.

Apple's AI chief steps down as company falls behind in tech race

The Bank of England warned that a multi-trillion dollar spending boom in artificial intelligence infrastructure financed by debt risks unraveling given “materially stretched” stock market valuations.

حذرت بنك إنجلترا من المخاطر المرتبطة بطفرة إنفاق تقدر بمليارات الدولارات في بنية الذكاء الاصطناعي، والتي تمول إلى حد كبير من خلال الديون. وأشارت البنك المركزي إلى أن التقييمات الحالية في سوق الأسهم 'ممتدة بشكل مادي'، مما يثير القلق بشأن استدامة هذا النمو.

El Banco de Inglaterra ha emitido una advertencia sobre los riesgos asociados con un auge de gasto de varios billones de dólares en infraestructura de inteligencia artificial, financiado en gran medida a través de deuda. El banco central destacó que las valoraciones actuales del mercado de valores están 'materialmente estiradas', lo que genera preocupaciones sobre la sostenibilidad de este crecimiento.

La Banque d'Angleterre a émis un avertissement concernant les risques associés à un boom de dépenses de plusieurs trillions de dollars dans l'infrastructure de l'intelligence artificielle, largement financé par la dette. La banque centrale a souligné que les valorisations actuelles du marché boursier sont 'matériellement étirées', soulevant des préoccupations quant à la durabilité de cette croissance.

The Bank of England has issued a warning regarding the risks associated with a multi-trillion dollar spending boom in artificial intelligence infrastructure that is largely financed through debt. The central bank highlighted that current stock market valuations are 'materially stretched', raising concerns about the sustainability of this growth.

Kai-Fu Lee's brutal assessment: America is already losing the AI hardware war to China

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