Recently the New York Times reported the following:
How China Built a Chip Industry, and Why It’s Still Not
Enough (2/2)
More than a decade into Beijing’s push for self
sufficiency, Chinese firms are producing fewer, lower-performing chips than
their foreign competitors.
The NYT - By Meaghan Tobin reporting from Taipei, Taiwan ;
Xinyun Wu contributed reporting from Taipei. Meaghan Tobin covers business and
tech stories in Asia with a focus on China and is based in Taipei.
Feb. 14, 2026, 12:00 a.m. ET
(continue)
Huawei’s Pivot
In 2014, China was the world’s largest market for
semiconductors. But 90 percent of the chips its companies used were made
outside the country.
Concerned about that dependency, the State Council, China’s
top governing body, approved a plan to spend billions and made a vow: China
would be making every part of its semiconductor supply chain at home by 2030.
Policymakers had reason to be concerned about the risks that
foreign technology posed to Chinese infrastructure. Earlier that year,
documents provided by the former National Security Agency contractor Edward J.
Snowden had disclosed that the U.S. government had monitored the communications
of top executives at Huawei.
Then in 2017, President Trump fined the Chinese
telecommunications giant ZTE for allegedly violating U.S. sanctions on Iran,
crippling its business overnight. Although ZTE does not manufacture chips, the
action gave China another lesson in its need for self reliance.
Next came Huawei. The first Trump administration embarked on
a global campaign to get countries to stop using Huawei’s equipment in their
telecommunications infrastructure. Huawei responded by offloading that business
line and getting in step with Beijing’s self-sufficiency program.
“Huawei was unique in its capabilities and its alignment
with China’s national goals,” said Kyle Chan, a fellow at the Brookings
Institution who studies Chinese industrial policy. “Huawei’s experience was a
microcosm of China’s broader experience: suddenly being cut off and now
scrambling to build its own.”
Beijing also pushed foreign companies to turn over
technology as a price of admission to the China market. Qualcomm, a San Diego
tech giant, entered into a joint venture with Huaxintong Semiconductor in 2016.
The Chinese government provided land and financing, and Qualcomm offered the
technology and about $140 million in initial funding.
During this time, Huawei became one of China’s most popular
smartphone makers. And it started working closely with chip factories to make
chips for smartphones and A.I. systems.
Huawei has come out with a line of chips that are comparable
to some of Nvidia’s older models. But analysts said those chips contained key
components that foreign rivals like TSMC and Samsung had made.
Clouds and Clusters
The inability to get essential tools from ASML has been a
major chokehold for Chinese chip makers. Since U.S. officials led an effort to
lobby the Dutch government to block shipments to China, no Chinese company has
been able to buy ASML’s most advanced tools.
Instead, Chinese chip makers have recruited engineers with
experience using those machines at TSMC, the world’s top chip maker. And now,
Chinese start-ups are trying to make their own chip manufacturing equipment.
A.I. systems require an immense amount of computing power to
learn. China’s A.I. companies are trying to get the computing power they need
by strapping together numerous less powerful chips. Huawei has taken such an
approach, and the Chinese government has built what it calls “intelligent
computing clusters” that are essentially state-run data centers.
But those clusters need a lot of chips. Experts and people
who work in the industry say China’s most advanced chip maker, Semiconductor
Manufacturing International Company, which does some work for Huawei, has
struggled to produce enough chips. The chips it does produce are prone to
defects and use more electricity than cutting-edge foreign ones. SMIC did not
respond to a request for comment.
“Manufacturing volume is going to be an issue,” said Kendra
Schaefer, a partner at Trivium China, a research and advisory firm.
Nonetheless, multiple Chinese A.I. researchers have reported
breakthroughs in finding new ways to link chips together for maximum
efficiency. Zhipu said last month that it had built its latest model entirely
using Huawei’s chips and software.
So far, the efficiency gains have been limited and have not
helped Chinese companies escape the fact that A.I. demands huge quantities of
chips.
Another way China’s A.I. companies are getting the computing
power they need is by paying cloud providers like Alibaba and Amazon for remote
access to massive data centers stocked with powerful chips.
But the strategy is expensive.
Documents filed by Zhipu and Minimax, another Chinese A.I.
start-up, with the Hong Kong Stock Exchange last month show that the two
companies are spending a lot more buying cloud services than they are earning
in revenue.
Translation
中國如何打造晶片產業,為何仍有所不足(2/2)
北京推進晶片自給自足已逾十年,但中國企業生產的晶片數量和性能卻不如外國競爭對手
(繼續)
華為的轉型
2014年,中國是全球最大的半導體市場。但其企業使用的晶片中,90%產自國外。
出於對這種依賴性的擔憂,中國最高決策機構國務院批准了一項數十億美元的計劃,並承諾:到2030年,中國將實現半導體供應鏈所有環節的自主生產。
中國政策制定者有理由擔憂外國技術對中國基礎設施構成的風險。同年早些時候,前美國國家安全局承包商Edward J. Snowden提供的文件披露,美國政府曾監聽華為高層的通訊。
隨後在2017年,特朗普總統以中國涉嫌違反美國對伊朗的製裁為由,對中國電信巨頭中興通訊處以罰款,一夜之間重創了其業務。儘管中興通訊並不生產晶片,但這項舉措再次讓中國認識到自力更生的必要性。
接下來是華為。特朗普第一屆政府發起了一場全球運動,要求各國停止在其電信基礎設施中使用華為的設備。華為的回應是剝離了該業務線,並配合北京的自給自足計劃。
布魯金斯學會研究中國產業政策的研究員Kyle
Chan表示:「華為的獨特之處在於其能力以及與中國國家目標的契合度」;「華為的經歷是中國整體經歷的一個縮影:突然被切斷聯繫,現在正努力構建自己的體系」。
北京也要求外國公司交出技術,以此作為進入中國市場的准入條件。總部位於聖地牙哥的科技巨頭Qualcomm於2016年與Huaxintong半導體成立了一家合資企業。中國政府提供土地和資金,而Qualcomm則提供技術和約1.4億美元的初期資金。
在此期間,華為成為中國最受歡迎的智能手機製造商之一。它開始與晶片工廠密切合作,為智能型手機和人工智能系統生產晶片。
華為推出了一系列晶片,其性能可與英偉達的一些早期型號相媲美。但分析師指出,這些晶片包含的關鍵組件是由台積電和三星等外國競爭對手生產的。
雲端和集群
一直是困擾中國晶片製造商的一大難題是無法從ASML獲得關鍵工具。自從美國官員主導遊說荷蘭政府阻止向中國出口ASML設備以來,沒有一家中國公司能夠購買ASML最先進的設備。
取而代之的是,中國晶片製造商從世界頂級晶片製造商台積電(TSMC)招募了擁有相關設備使用經驗的工程師。如今,中國新創公司正嘗試自行研發晶片製造設備。
人工智能系統需要強大的運算能力才能進行學習。中國的人工智能公司正試圖透過將眾多性能較低的晶片組合在一起來獲得所需的運算能力。華為就採用了這種方法,而中國政府也建造了所謂的“智能計算集群”,這些集群本質上是國有數據中心。
但這些集群需要大量的晶片。專家和業內人士表示,中國最先進的晶片製造商 - 中芯國際(SMIC),它為華為提供部分晶片製造服務 - 一直難以生產足夠的晶片。中芯國際生產的晶片缺陷率高,而且比國外最先進的晶片耗電量更大。中芯國際未對此置評。
研究顧問公司
Trivium China 的合夥人
Kendra Schaefer 表示:「產量將是一個問題」。
儘管如此,多位中國人工智能研究人員報告稱,他們在尋找將晶片連接起來以實現最高效率的新方法方面取得了突破。智普人工智能(Zhipu AI) 上個月表示,其最新型號完全使用了華為的晶片和軟件。
到目前為止,效率提升有限,也未能幫助中國企業擺脫人工智能需要大量晶片的困境。
中國的人工智能公司是獲取所需運算能力的另一種方式是向阿里巴巴和亞馬遜等雲端服務供應商付費,利用遠端去用配備有強大晶片的大型數據中心的服務。
但這種策略成本高。
智普(Zhipu
AI)和另一家中國人工智能新創公司 Minimax 上個月向香港證券交易所提交的文件顯示,這兩家公司在購買雲端服務上的支出遠遠超過了它們的收入。
So, in the development of AI, one thing was
holding back China: They needed more superfast semiconductors. China’s most
advanced chip maker has struggled to produce enough chips. The chips it does
produce are prone to defects and use more electricity than cutting-edge foreign
ones. One solution for China’s A.I. companies is to get the computing power
they need by paying cloud providers such as Alibaba and Amazon for their services, but the strategy is expensive. Apparently, China is facing a dilemma in its development
in AI.