{"id":261313,"date":"2025-11-04T05:42:11","date_gmt":"2025-11-04T05:42:11","guid":{"rendered":"https:\/\/www.newsbeep.com\/au\/261313\/"},"modified":"2025-11-04T05:42:11","modified_gmt":"2025-11-04T05:42:11","slug":"is-china-about-to-win-the-race","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/au\/261313\/","title":{"rendered":"is China about to win the race?"},"content":{"rendered":"

This article is an on-site version of our The State of AI newsletter. Sign up here<\/a> to get the newsletter sent straight to your inbox every Monday. Explore all of our newsletters here<\/a><\/p>\n

Welcome to The State of AI, a new collaboration between the Financial Times and MIT Technology Review. Every Monday for the next six weeks, writers from both publications will debate one aspect of the generative AI revolution reshaping global power. <\/p>\n

This week, John Thornhill, FT tech columnist and Innovation Editor and Caiwei Chen, MIT Technology Review\u2019s China reporter, ask whether China can beat the US in the battle for technological supremacy. <\/p>\n

Do you agree Beijing is on course to overtake Silicon Valley? Join John in a live Q&A on November 13 at 1pm GMT. You can submit a question ahead of time here.<\/a><\/p>\n

John Thornhill writes<\/p>\n

Viewed from abroad, it seems only a matter of time before China emerges as the AI superpower of the 21st century.\u00a0<\/p>\n

In the west, our initial instinct is to focus on the US\u2019s significant lead in semiconductor expertise, its cutting-edge AI research and its vast investments in data centres. The legendary investor Warren Buffett once warned: \u201cNever bet against America.\u201d He is right that, for more than two centuries, no other \u201cincubator for unleashing human potential\u201d has matched the US.<\/p>\n

Today, however, China has the means, motive and opportunity to commit the equivalent of technological murder. When it comes to the mobilisation of the whole-of-society resources needed to develop and deploy AI to maximum effect, it may be just as rash to bet against China.\u00a0<\/p>\n

The data highlights the trends. In AI publications and patents, China leads. By 2023, China accounted for 22.6 per cent of all citations, compared with 20.9 per cent from Europe and 13 per cent from the US, according to Stanford University\u2019s Artificial Intelligence Index Report 2025<\/a>. As of 2023, China also accounted for 69.7 per cent of all AI patents. True, the US maintains a strong lead in the top 100 most cited publications (50 vs 34 in 2023) but its share has been steadily declining.\u00a0<\/p>\n

The US also outdoes China in top AI research talent \u2014 but the gap is narrowing. According to a report from the US Council of Economic Advisers<\/a>, 59 per cent of the world\u2019s top AI researchers worked in the US in 2019, compared with 11 per cent in China. But by 2022 that ratio was 42 per cent to 28 per cent.\u00a0<\/p>\n

The Trump administration\u2019s tightening of restrictions for foreign H-1B visa holders may well lead to more Chinese AI researchers in the US returning home. The talent ratio could move further in China\u2019s favour.<\/p>\n

Regarding the technology itself, US-based institutions produced 40 of the world\u2019s most notable AI models in 2024, compared with 15 from China. But Chinese researchers have learned to do more with less, and their strongest large language models \u2014 including the open-source DeepSeek-V3 and Alibaba\u2019s Qwen 2.5-Max \u2014 surpass the best US models in terms of algorithmic efficiency.<\/p>\n

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Where China is really likely to excel in future is in applying these open-source models. The latest report from Air Street Capital shows that China has now overtaken the US in terms of monthly downloads of AI models. In AI-enabled fintech, ecommerce and logistics, China already outstrips America.\u00a0<\/p>\n

Perhaps the most intriguing \u2014 and potentially the most productive \u2014 applications of AI may yet come in hardware, particularly in drones and industrial robotics. With the research field evolving towards embodied AI, China\u2019s advantage in advanced manufacturing will shine through.<\/p>\n

Dan Wang, tech analyst and author of Breakneck: China\u2019s Quest to Engineer the Future, has rightly highlighted the strengths of China\u2019s engineering state in manufacturing \u2014 even if he has also shown the damaging effects of applying that engineering mentality in the social sphere. \u201cChina has been growing technologically stronger and economically more dynamic in all sorts of ways,\u201d he told me. \u201cBut repression is very real. And it is getting worse in all sorts of ways as well.\u201d<\/p>\n

I\u2019d be fascinated to hear from you, Caiwei, about your take on the strengths and weaknesses of China\u2019s AI dream. To what extent will China\u2019s engineered social control hamper its technological ambitions?\u00a0<\/p>\n

Caiwei Chen responds <\/p>\n

Hi John!<\/p>\n

You\u2019re right that the US still holds a clear lead in frontier research and infrastructure. But \u201cwinning\u201d AI can mean many different things. Jeffrey Ding, in his book Technology and the Rise of Great Powers, makes a counterintuitive point: for a general-purpose technology such as AI, long-term advantage often comes down to how widely and deeply technologies spread across society. And China is in a good position to win that race (although murder might be pushing it a bit!).<\/p>\n

Chips will remain China\u2019s biggest bottleneck. Export restrictions have throttled access to top GPUs, pushing buyers into grey markets and forcing labs to recycle or repair banned Nvidia stock. Even as domestic chip programmes expand, the performance gap at the very top still stands.<\/p>\n

Yet those same constraints have pushed Chinese companies towards a different playbook<\/a>: pooling compute, optimising efficiency and releasing open-weight models. DeepSeek-V3\u2019s training run, for example, used just 2.6mn GPU-hours \u2014 far below the scale of US counterparts. But Alibaba\u2019s Qwen models now rank among the most downloaded open weights globally, and companies such as Zhipu and MiniMax are building competitive multimodal and video models.\u00a0<\/p>\n

China\u2019s industrial policy means new models can move from lab to implementation fast. Local governments and big enterprises are already rolling out reasoning models in administration, logistics and finance.\u00a0<\/p>\n

Education is another tell. Major Chinese universities are implementing AI literacy programmes<\/a> in their curricula, embedding skills proactively before the labour market demands them. The Ministry of Education has also announced plans to integrate AI training for children of all school ages. I\u2019m not sure \u201cengineering state\u201d fully captures China\u2019s relationship with new technologies, but decades of infrastructure building and top-down co-ordination have made the system unusually effective at pushing large-scale adoption, often with far less social resistance than you would see elsewhere. The use at scale, naturally, allows for faster iterative improvements.<\/p>\n

The public in China feels the same. Stanford HAI\u2019s 2025 AI index<\/a> found Chinese respondents to be the most optimistic in the world about AI \u2014 far more than in the US or the UK. This is striking, given that China\u2019s economy has slowed since the Covid pandemic for the first time in more than two decades. Many in government and industry now see AI as a much-needed spark. Optimism can be a powerful fuel, but whether it can sustain through slower growth is still an open question.<\/p>\n

Social control remains part of the picture, but a different kind of ambition is taking shape. The new generation of Chinese AI founders are the most globally minded I\u2019ve seen, moving fluidly between Silicon Valley hackathons and pitch meetings in Dubai, many fluent in English and in the rhythms of global venture capital. Having watched the last generation wrestle with the burden of a Chinese label, they now build companies that are quietly transnational from the start.<\/p>\n

The US may still lead in speed and experimentation, but China could shape how AI becomes part of daily life, both at home and abroad. Speed matters, but speed isn\u2019t the same thing as supremacy.<\/p>\n

John Thornhill replies <\/p>\n

It\u2019s true, Caiwei, that speed is not the same as supremacy (and murder may be too strong a word). And you\u2019re also right to amplify the point about China\u2019s strength in open-weight models and the US preference for proprietary models. This is not just a struggle between two different countries\u2019 economic models but also between two different ways of deploying technology.\u00a0\u00a0<\/p>\n

Even OpenAI\u2019s chief executive Sam Altman admitted earlier this year<\/a>: \u201cWe have been on the wrong side of history here and need to figure out a different open-source strategy.\u201d That\u2019s going to be a very interesting subplot to follow. Who\u2019s called that one right?<\/p>\n

Further reading <\/p>\n

When it comes to real-world uses, toys and companion devices, the MIT Technology Review reveals how a novel but emergent application of AI is gaining traction in China<\/a> <\/p>\n

The once-frantic data centre build-out in China has hit walls, and as the sanctions and AI demands shift, this on-the-ground reporting<\/a> from MIT Technology Review looks at how stakeholders are figuring it out<\/p>\n

There\u2019s still time to save your spot at the FT\u2019s Future of AI Summit on November 5-6, featuring Nvidia\u2019s Jensen Huang and 600 business leaders involved in AI application. Register for an in-person pass at this year\u2019s summit here<\/a>\u00a0 <\/p>\n

Recommended newsletters for you<\/p>\n

The AI Shift \u2014 John Burn-Murdoch and Sarah O\u2019Connor dive into how AI is transforming the world of work. Sign up here<\/a><\/p>\n

Newswrap \u2014 Our business and economics round-up. Sign up here<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"This article is an on-site version of our The State of AI newsletter. Sign up here to get…\n","protected":false},"author":2,"featured_media":261314,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[256,254,255,64,63,105],"class_list":["post-261313","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-au","tag-australia","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/261313","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/comments?post=261313"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/261313\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media\/261314"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media?parent=261313"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/categories?post=261313"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/tags?post=261313"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}