Nvidia CEO Jensen Huang has admitted to having an affair, reportedly with a Chinese executive at a Singapore-based company that the United States suspects of smuggling AI microchips into China.<\/p>\n
The scandal has focused attention on how China, a major artificial-intelligence power in itself, obtains the cutting-edge chips despite US export restrictions.<\/p>\n
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<\/div>\n<\/div>\n<\/div>\nWhy are Nvidia chips so important?<\/h4>\n
Nvidia designs advanced components originally created to handle 3D visuals in video games, called Graphics Processing Units (GPUs).<\/p>\n
These have the power to crunch colossal amounts of digital data, so are also used at scale to train and run artificial intelligence.<\/p>\n
ChatGPT’s 2022 launch showcased the potential of AI, sparking an investment gold rush as governments and tech giants raced to develop the technology further.<\/p>\n
With chip orders pouring in, Nvidia’s market valuation has soared to $4.5 trillion — currently on par with Apple as the world’s two most valuable companies.<\/p>\n
Which chips does the US restrict?<\/h4>\n
Washington bans the export of Nvidia’s top-end “Blackwell” and “Rubin” GPUs to China, citing security concerns, as advanced AI has military applications.<\/p>\n
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<\/div>\n<\/div>\n<\/div>\nThe policy also allows the United States’s top AI labs to maintain their global lead.<\/p>\n
Huang has lobbied the U.S. government to allow Nvidia chip sales to China, warning that the restrictions are fuelling the rise of competitive homegrown alternatives.<\/p>\n
This year, Washington eased controls on Nvidia’s previously banned — and less powerful — “H200” chip, with the United States taking a 25% cut of sales.<\/p>\n
But U.S. conditions have made it difficult for shipments to be approved, with Beijing also reportedly reluctant to buy H200s as its own chip industry gains momentum.<\/p>\n
How does China get its chips?<\/h4>\n
Recent launches of high-performing models from Chinese startups, including Moonshot AI, Z.ai and DeepSeek, have turned up the heat on U.S. rivals.<\/p>\n
“Chinese vendors are still using cutting-edge Nvidia chips to train their models” despite the controls, Lian Jye Su, a chief analyst at Omdia, told AFP<\/i>.<\/p>\n
Chips may be smuggled into the country, or accessed through a loophole that allows Chinese firms to rent out computing power at data centres stuffed with Nvidia chips in a third nation, often Southeast Asian.<\/p>\n
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<\/div>\n<\/div>\n<\/div>\n“U.S. export controls restrict where a chip is shipped, not who uses it,” explained Stephen Wu, founder of the Carthage Capital investment fund.<\/p>\n
That means Nvidia GPUs can sit in Malaysia’s Johor region, for example, “in full compliance while a customer in Shenzhen logs in”, Wu told AFP<\/i>.<\/p>\n
White House adviser Michael Kratsios said this summer that Moonshot AI had accessed high-end Nvidia chips in Thailand.<\/p>\n
Washington has also accused Chinese AI labs of training systems to mimic the capabilities of US models.<\/p>\n
And then there is the big question of smuggling.<\/p>\n
Tech outlet The Information said in December that DeepSeek developed its new model using thousands of chips dismantled overseas and brought into China.<\/p>\n
DeepSeek did not respond to a comment request at the time. Nvidia told The Information they had not seen evidence of such smuggling which “seems far-fetched”.<\/p>\n
How about Chinese chips?<\/h4>\n
“Nvidia chips still make top-level AI work faster and easier, but they are no longer the only path,” said Poe Zhao, founder of analysis publication Hello China Tech.<\/p>\n
“The open question is cost” as “training on Chinese chips usually takes more time and more engineering”.<\/p>\n
Huawei is China’s top Nvidia competitor, although it lags behind the U.S. titan, and DeepSeek will reportedly train its next major AI model on Huawei chips.<\/p>\n
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<\/div>\n<\/div>\n<\/div>\n“Chinese-made chips are improving fast”, Su said, with more collaborations likely to come.<\/p>\n
Huawei said in September its next-generation AI chip would be ready in the first quarter of 2027, three quarters earlier than planned.<\/p>\n
To boost the power of Chinese-made chips, AI companies need to use more of them, Wu said.<\/p>\n
“They pay for it in power and cost — which they can afford, because Chinese electricity is cheap and the chips are state-subsidised.”<\/p>\n<\/div>\n