China’s Lesson for the Artificial Super Intelligence Overtakes AI

The AI war is increasingly waged among ‘hyperscalers’ – companies with full-stack capabilities across software, hardware and applications

Strategic Shift Toward Full-Stack AI

· Alibaba CEO Eddie Wu unveiled a roadmap to become the world’s leading full-stack AI service provider, targeting artificial superintelligence (ASI).

· The strategy includes open-source models (Qwen), cloud infrastructure, and global data center expansion.

Investment and Hyperscaler Dynamics

· US and Chinese tech giants are projected to spend over $400 billion on AI infrastructure in 2025.

· US hyperscalers (AWS, Azure, Google) dominate 63% of the global cloud market; Alibaba Cloud leads in China with 36%.

· OpenAI’s partnerships and funding commitments exceed $1 trillion, dwarfing Alibaba’s $53 billion pledge.

China’s “AI Plus” Industrial Strategy

· China integrates AI into manufacturing, logistics, and robotics—termed “embodied intelligence”.

· It leads the world in industrial robot installations (2.027 million active units).

· Government support channels nearly 50% of AI fundraising into robotics startups.

Parallel Ecosystems and Open-Source Leadership

· China’s AI ecosystem is parallelized, with Alibaba, Huawei, Baidu, ByteDance serving diverse market segments.

· Chinese models excel in image/video generation and dominate global leaderboards at lower training costs.

· Open-source platforms like DeepSeek and Alibaba saw download surges of 1,000% and 135%, respectively.

Hardware Independence and Strategic Alignment

· China is building a self-sufficient AI stack, reducing reliance on Nvidia and US chips.

· DeepSeek’s new programming language TileLang received immediate support from Chinese chipmakers.

· Huawei is developing core operators to support this ecosystem.

US Focus on AGI and Export Controls

· US strategy centers on achieving AGI first, with heavy investment in compute scaling and chip export restrictions.

· Critics argue this focus may neglect application-level adoption and full-stack development.

· OpenAI and others are now expanding into robotics and autonomous systems to catch up.

[ABS News Service/13.10.2025]

When Alibaba Group Holding’s CEO Eddie Wu Yongming took the stage at the company’s annual Apsara conference in Hangzhou on September 24, few people expected the media-shy executive to deliver anything shocking, especially since he read from prepared statements at last year’s event.

Wu, however, immediately outlined a clear road map for Alibaba’s AI development, with a goal towards so-called artificial superintelligence (ASI) – when the firm’s Qwen open-source models and cloud services would serve as the software and computing infrastructure of the future.

In essence, Alibaba aimed to become the “world’s leading full-stack AI service provider”, he said. Alibaba owns the Post.

The blueprint laid out in Wu’s 23-minute speech signified not just a strategic upgrade for Alibaba, but also highlighted the competition between Chinese and US tech giants for the future of artificial intelligence – a field that has drawn some of the largest investments in history, with profound economic, social and geopolitical implications.

As he spoke, Alibaba’s shares surged to a four-year high in Hong Kong, leading several banks to raise their price targets for the stock.

A day later, US chipmaker Nvidia’s co-founder and CEO Jensen Huang referenced Wu’s remarks during a podcast with tech investors Brad Gerstner and Bill Gurley, in which he underscored the importance of spending big on AI.

When asked about Nvidia’s US$100 billion investment in OpenAI, Huang predicted that the ChatGPT maker could become a “multi-trillion-dollar hyperscale company” on the back of its rapidly expanding array of products.

The AI arena has now shifted from just large language models to include upstream hardware and downstream applications, according to Kyle Chan, a postdoctoral researcher at Princeton University.

China was engaged in a “different AI race” from the US, and it was no longer enough to have the strongest foundational model: one must also possess the best chips, algorithms and applications across the entire AI stack to stand out in a crowded field, Chan said.

“Only in a pure ‘race to AGI’ world would the US be miles ahead, but that is probably not the world we live in,” he said, referring to artificial general intelligence – a hypothetical AI system capable of matching human performance in economically valuable tasks.

Some estimates suggested that US and Chinese tech giants would collectively spend more than US$400 billion on AI infrastructure this year – roughly equivalent to the gross domestic product of Romania, the world’s 39th-largest economy according to the International Monetary Fund.

That prompted some analysts to argue that the AI competition between China and the US was now being waged by “hyperscalers” – the world’s largest tech companies with major capabilities across the entire AI stack.

Both Washington and Beijing have voiced support for their respective AI industries. The Trump administration’s AI Action Plan, released in July, aimed to promote the export of “American AI” technology globally, led by Nvidia and OpenAI – the world’s most valuable company and start-up, respectively.

As part of their partnership, Nvidia is helping OpenAI establish its own “self-hosted” data centres, which the start-up previously relied on Microsoft to provide. The move could also allow OpenAI to catch up with Tesla founder Elon Musk’s xAI, which is building its own Colossus data centres in Memphis, Tennessee.

Alongside its recent deals with Advanced Micro Devices (AMD) and Samsung Electronics, as well as the US$500 billion in pledged funding for the Stargate Project – OpenAI’s joint venture with SoftBank Group and Oracle – the start-up’s computing deals amounted to at least US$1 trillion this year.

More partnerships could be announced “in the coming months”, OpenAI CEO Sam Altman said on a podcast on Thursday.

“To make the bet at this scale, we kind of need the whole industry, or a big chunk of the industry, to support it,” he said. “And this is from the level of electrons to model distribution and all the stuff in between, which is a lot.”

China, too, has its share of hyperscalers, but their size lags behind their US counterparts. The big three American players – Amazon Web Services, Microsoft Azure and Google – command about 63 per cent of the US$900 billion global cloud computing market, according to Synergy Research Group.

In China, Alibaba’s AI and cloud computing arm Alibaba Cloud holds a clear lead with 36 per cent of the market, according to research firm Omdia.

At last month’s conference, Wu announced additional AI infrastructure spending beyond the initial US$53 billion commitment unveiled earlier this year. The company hinted that these extra funds would support the company’s largest overseas data centre expansion to date, including its first hubs in Brazil, France and the Netherlands. Wu said demand overseas “far exceeded” domestic growth.

Meanwhile, Alibaba’s semiconductor design unit T-Head has developed an AI processor comparable to Nvidia’s H20 – a chip tailored for China-based customers to meet US export curbs – according to a report by the mainland’s state broadcaster last month.

Despite their advances, Chinese companies remained significantly behind their US peers in terms of investment. Alibaba’s three-year spending pledge is less than what any one of the US big three hyperscalers spends in a single year.

OpenAI is currently valued at US$500 billion, while US AI model developer Anthropic saw its valuation nearly triple to US$183 billion following a funding round in September. In contrast, China’s leading start-ups, such as Moonshot AI and Z.ai, are valued at US$3.3 billion and US$5.6 billion, respectively.

That did not necessarily mean China was falling behind in AI, Princeton’s Chan said. In the US, Silicon Valley executives – including Altman – stressed the urgency of beating China to achieve AGI.

The US preoccupation with achieving AGI before China had led to an excessive focus on scaling computing resources and restricting Chinese access to advanced semiconductors, at the expense of developing the full US stack, Chan said.

“Chinese policymakers are not ‘AGI-pilled’,” he said. “I think they see AI as something like the internet that can turbocharge, if not transform, existing industries, where the focus is on diffusing the technology broadly and increasing adoption,” said Chan, adding that he did not believe AGI was imminent.

Alibaba chairman Joe Tsai, meanwhile, has stressed the importance of adoption. At an event hosted by the US podcast All-In last month, he said the winner in AI should not be defined by “who comes up with the strongest AI model”, but on “who can adopt it faster”.

“I’m not saying China technologically is winning the model war,” he said. “But in terms of the actual application and also people benefiting from AI, it has made a lot of developments.”

The Chinese government is betting on the integration of AI with the country’s formidable industrial and manufacturing sectors to win the tech race, a strategy known as “AI plus”.

China now leads the world in industrial robot installations, with a record 2.027 million active robots, according to the International Federation of Robotics.

The country’s humanoid robot market has also seen rapid growth, with prominent start-ups like Shanghai-based AgiBot and Hangzhou-based Unitree Robotics landing orders from state-owned firms.

In March, for the first time, Beijing designated “embodied intelligence” – AI integrated into physical machines – as a key future industry. Authorities later outlined plans to promote robotics adoption across various sectors, including manufacturing, aerospace and logistics.

Government support has filtered down to the entrepreneurial level, with nearly half of AI fundraising this year directed towards embodied intelligence start-ups, according to consultancy IT Juzi.

“China is running away with the hard-power part of AI – robotics,” Martin Casado and Anne Neuberger, a general partner and senior adviser, respectively, at Silicon Valley venture capital firm Andreessen Horowitz, said in a recent post.

“We start seeing intelligence embedded in the physical world – culminating in generalist robots that perform a wide variety of tasks across applications, from manufacturing to services to defence,” they wrote. “The country betting on that future is China, not the US.”

Signs indicate that the US increasingly recognises the importance of AI applications in hard technology. OpenAI is reportedly ramping up hires for its robotics team and has partnered with autonomous driving start-up Applied Intuition.

However, none of the world’s “big four” industrial robotics firms – ABB Robotics, Fanuc, Kuka and Yaskawa Electric – are based in the US.

The spending disparity between Silicon Valley and Chinese firms may not be critical, as Chinese hyperscalers do not always compete directly with their US counterparts, according to Poe Zhao, a Beijing-based tech analyst and founder of the Hello China Tech newsletter.

“At least in the AI field, the market has become completely parallelised, with each playing its own game,” he said. “I think many people in the English-speaking world do not understand just how big the Chinese cloud market really is, with many demands from different segments, from large state-owned enterprises to small and medium-sized enterprises.”

“It is impossible for any company to be like Amazon – to be a one-stop shop that meets everyone’s needs, which gives Alibaba, Huawei, Baidu and ByteDance different opportunities.”

It also remained unclear just how far ahead US foundational models were compared to their Chinese rivals, according to Tilly Zhang, a Beijing-based tech analyst at Gavekal Dragonomics.

Chinese models consistently top popular global AI leader boards, particularly in image and video generation, often delivering comparable performance at a fraction of the training costs of US competing products.

The US government acknowledged the potential of China’s open-source ecosystem in driving global adoption.

According to a report last week from the Centre for AI Standards and Innovation at the National Institute of Standards and Technology and the Department of Commerce, downloads of models from DeepSeek and Alibaba on the developer platform Hugging Face had surged nearly 1,000 per cent and 135 per cent, respectively, since January.

Meanwhile, partners at Andreessen Horowitz pointed out that US start-ups and universities were heavily reliant on Chinese models.

The AI Action Plan emphasised the need for the US to develop leading open-source models, as the country’s previous open-source leader, Facebook owner Meta Platforms, has signalled it is no longer interested in open-sourcing its Llama models.

OpenAI swiftly responded to the government’s call in August with its first open model in six years, but the gap with China’s well-established ecosystem – similar to that in robotics – may already be too wide to bridge, according to open-source AI expert Nathan Lambert.

“Qwen alone is roughly matching the entire American open model ecosystem today”, Lambert said at a recent industry conference.

He highlighted the depth of China’s open-source ecosystem, which spans from Big Tech giants such as Huawei Technologies and ByteDance to unexpected developers like food delivery giant Meituan and Alibaba’s fintech affiliate Ant Group, which open-sourced a 1 trillion-parameter model on Thursday.

Just as OpenAI has allied itself with Nvidia and AMD, a self-sufficient AI ecosystem is emerging in China through a collaboration between Huawei and DeepSeek.

In the latest example, when DeepSeek introduced a new programming language called TileLang as part of its new foundational model, Hygon Information Technology and Cambricon Technologies quickly announced “day zero” chip support for the new model, while Huawei said it was developing core operators for TileLang.

“This synchronicity suggests a strategic alignment,” Hello China Tech’s Zhao said. “It is the second phase of a deliberate campaign to build a self-sufficient AI stack, free from Nvidia’s influence.”

The jury is still out on whether Chinese AI players can achieve ASI with local hardware, although Huawei touted that its clustering solution could address computing power needs.

Meanwhile, American lawmakers have called for broader chip export controls, believing access to US technologies remains crucial for China’s AI ambitions.

At the Apsara conference, hundreds of developers and customers listened intently to the presentations, many using a Qwen-powered translation and transcription tool. Alibaba appeared undeterred, as it stressed its commitment to cultivating a vibrant AI ecosystem.

There would only be “five or six hyperscalers globally” in the future, Wu said, implying that Alibaba would be one of them.