Huawei in AI Partnership with DeepSeek
Before this week’s U.S.-Chinese summit, Beijing
reached a milestone in its quest for technological self-sufficiency.
·
The move reduces dependence on American AI
hardware, especially chips made by Nvidia, which currently dominate the global
AI market.
·
The announcement comes ahead of a summit between
Donald Trump and Xi Jinping, strengthening Beijing’s position in ongoing
technology and trade tensions.
·
US export controls were designed to slow China’s AI
progress by limiting access to advanced Nvidia chips, but Chinese firms are
increasingly adapting to those restrictions rather than waiting for them to be
lifted.
·
Analysts say the restrictions are encouraging China
to build an independent AI ecosystem, including domestic chips, software and
infrastructure.
·
DeepSeek said Huawei chips are being used for
“inference” — the process that allows AI systems to generate responses for
users.
·
However, DeepSeek reportedly still used Nvidia
chips to train its AI model, according to semiconductor industry sources.
·
Chinese firms can still remotely access Nvidia
chips located in overseas data centres, despite US restrictions.
·
Huawei has announced plans to release an AI
training chip this year, though it says matching Nvidia’s top performance may
still take another year.
·
Jensen Huang has repeatedly warned that strict US
export controls could create a split global AI ecosystem:
o
Chinese AI systems powered by Chinese chips,
o
Western systems powered by American technology.
·
Huang argues that excessive restrictions could
ultimately weaken US influence over China’s AI sector.
·
Although Trump later allowed Nvidia to sell H200 AI
chips to China, uncertainty remains over whether significant shipments will
occur.
·
US Commerce Secretary Howard Lutnick recently
stated that no H200 chips had yet been delivered to China.
·
China continues pushing domestic alternatives
despite manufacturing challenges faced by Semiconductor Manufacturing
International Corporation, also known as SMIC.
·
SMIC’s chips reportedly:
o
have lower production yields,
o
consume more power,
o
and remain less advanced than foreign rivals’
products.
·
Huawei has attempted to compensate by linking
together large numbers of weaker chips to achieve higher computing power.
·
Before US restrictions tightened, many Huawei chips
were manufactured by Taiwan Semiconductor Manufacturing Company, the world’s
leading advanced chip producer.
·
Analysts say China is now redefining AI competition
by focusing not only on raw computing power, but also on building tightly
integrated ecosystems of chips, AI models and applications.
·
Huawei and DeepSeek are reportedly collaborating
closely so that hardware and software can be optimized together for better AI
performance.
·
Experts believe this strategy could help China
remain competitive in AI despite limited access to the most advanced Western
semiconductors.
[ABS News Service/12.05.2026]
When
the Chinese start-up DeepSeek released its latest artificial intelligence model
last month, it edged Beijing closer to a future that it has spent years trying to
build.
In
a small but meaningful break from American technology, DeepSeek said for the first
time that its new model had been optimized to run on chips made by the Chinese tech
giant Huawei. This was a milestone in China’s long-running effort to develop advanced
technologies at home and reduce its reliance on Western innovation.
While
most of the world’s leading A.I. systems still rely on semiconductors from the U.S.
chip-making giant Nvidia, Chinese A.I. firms are increasingly turning to homegrown
alternatives.
The
timing of DeepSeek’s announcement — before this week’s scheduled summit between
President Trump and Xi Jinping, China’s leader — gives Beijing fresh confidence
entering trade talks that U.S. export controls on Nvidia chips have not derailed
China’s A.I. development.
Any
meaningful shift by China away from American A.I. technology could limit the impact
of U.S. export controls and deprive Washington of a critical source of leverage
over Beijing. That prospect gained urgency since DeepSeek’s A.I. technology rattled
the U.S. tech industry and turned the company into a potent symbol of China’s drive
for technological self-sufficiency.
Before
last year’s meeting between the two leaders, Mr. Trump said he planned to discuss
Nvidia’s most powerful A.I. chips with Mr. Xi, fueling
speculation that the United States might ease restrictions on the technology.
But
after years of Washington’s preventing Chinese companies from buying certain advanced
technology products, firms like DeepSeek and Moonshot AI are starting to design
their A.I. systems around the constraints rather than waiting for them to disappear.
That includes exploring how their models can run on a broader range of processors
beyond Nvidia’s.
“U.S.
export controls are not freezing China’s A.I. development,” said Wei Sun, a principal
A.I. analyst at Counterpoint Research in Beijing. “They are forcing China to build
an alternative stack.”
DeepSeek
has said its latest model can use Huawei chips for inference, the process that allows
an A.I. system to respond more quickly and accurately to users. Inference generally
requires less computing power than training, the demanding process of teaching a
model how to function. DeepSeek still relied on Nvidia chips to train its system,
according to two people in the semiconductor industry who were not authorized to
comment publicly on the matter.
It
was not immediately clear how DeepSeek gained access to those chips, though Chinese
companies can still remotely use Nvidia chips housed in data centers outside China. DeepSeek did not respond to a request
for comment.
Huawei
has said it plans to release a chip for training this year. But it also said it
would take another year after that before its products could match the performance
of Nvidia’s current offerings.
The
growing split between Chinese and American A.I. infrastructure is a consequence
that Jensen Huang, Nvidia’s chief executive, has long warned would result from rigid
export controls.
He
has said the restrictions have only pushed Chinese companies to accelerate efforts
to build domestic alternatives, which could lead to a bifurcated market: Chinese
A.I. systems running on Chinese chips while the West sticks with American hardware.
As
the world’s dominant maker of A.I. chips, Nvidia stands to gain from unfettered
access to China. But Mr. Huang has argued that the strict restrictions will ultimately
hurt the United States by diminishing its influence over China’s A.I. industry.
Two
months after his last meeting with Mr. Xi, Mr. Trump granted Nvidia permission to
sell the H200, one of its most powerful chips, to China.
But
since then, those chips have been squeezed between lawmakers in Washington, who
are seeking closer oversight of their use in China, and Beijing, which has directed
Chinese tech companies to buy domestic chips.
Commerce
Secretary Howard Lutnick told a Senate Appropriations Committee last month that
no H200s had actually gone to China, and Nvidia said in regulatory filings this
year that it had yet to generate any revenue from H200 sales there. Ahead of this
week’s summit in Beijing, the fate of Nvidia’s chips in China is no clearer than
it was at the last meeting between Mr. Trump and Mr. Xi.
Analysts
expect that China’s frustration with U.S. export controls will be part of the discussion
when the two leaders meet.
“Chip
export controls have consistently been an issue China opposes,” said Jiang Tianjiao,
an associate professor at Fudan University in Shanghai. But as China’s chip-making
abilities improve, officials may not want to interfere with efforts to reduce its
dependence on American technologies, he said.
While
Chinese technology companies have continued to release high-performing A.I. systems
despite export controls, China’s push for technological self-sufficiency in chip
manufacturing still faces significant hurdles. Semiconductor Manufacturing International
Corporation, or SMIC, the Chinese company making some Huawei chips, has struggled
to produce them at scale. The chips it manufactures are more prone to defects and
consume more power than those made by foreign rivals.
Huawei’s
workaround has been to strap together large numbers of these weaker chips to achieve
the computing power of more advanced processors — a strategy that depends on SMIC’s
being able to manufacture in large volumes. Yet Chinese chipmakers are still expected
to produce only a small fraction of the advanced semiconductors made by foreign
companies like Nvidia this year.
Before
Washington tightened controls, many of Huawei’s chips were made by Taiwan Semiconductor
Manufacturing Company, which produces most of the world’s advanced chips, including
Nvidia’s.
Export
controls have constrained China’s ability to make the large volumes of advanced
chips needed for A.I., said Dan Kim, chief strategy officer at TechInsights, a Canadian research firm, and a Commerce Department
official during the Biden administration. But he added that those same restrictions
had also pushed Chinese tech companies to innovate in new ways.
Chinese
companies are trying to redefine what determines success in the race to build cutting-edge
A.I. For years, the industry’s most advanced systems have come from companies that
can afford to spend billions of dollars assembling vast numbers of powerful chips.
Now,
companies like Huawei are betting that success could someday depend less on amassing
the most computing power and more on building an integrated ecosystem of chips,
A.I. models and applications that is good enough for most real-world uses. By working
closely with A.I. model developers like DeepSeek, Huawei can customize its hardware
to better support the software running on it.
When
DeepSeek announced its latest model, Huawei said there had been “close collaboration
of chip and model technologies from both parties.”
In
technical papers describing its models, DeepSeek outlined specific ways chip makers
could modify their products to improve performance with its systems.
“DeepSeek is calling out into the void to Huawei
and other companies, ‘Please make these changes so we can get better performance
out of your chips,’” said Jacob Feldgoise, an analyst at the Center for Security and Emerging Technology at Georgetown University.