Chip giant TSMC opens first Japan factory as it diversifies away from Taiwan amid U.S.-China tensions
A general view shows the new semiconductor plant by Japan Advanced Semiconductor Manufacturing Company (JASM), a subsidiary of Taiwan’s chip giant TSMC.
Philip Fong | Afp | Getty Images
Taiwan Semiconductor Manufacturing Company opened its first chip plant in Japan on Saturday as it diversifies supply chains away from Taiwan amid intensifying U.S.-China trade tensions.
TSMC, which is the world’s largest contract chip manufacturer with clients such as Nvidia and Apple, has been courted by Europe, the U.S. and other countries to set up local operations.
Paul You, chairman of First Securities Investment Corporation said last month that the global semiconductor industry including Taiwan’s could be at risk from the U.S.-China chip war.
“I do believe the escalation between U.S. and China, especially like the chip war, will become higher and higher and that will dampen the growth for the global semiconductor [industry],” said You.
Located in Kumamoto, the chip fabrication plant in Japan will be equipped with a cleanroom — a controlled and sterile environment critical for chip making — with about 45,000 square meters of area, with production expected to start by the end of 2024, TSMC said.
Japan Advanced Semiconductor Manufacturing Inc., the manufacturing company majority-owned by TSMC, began construction of the plant in April 2022.
JASM was set up in Japan in 2021 with support from the Japanese government, Sony Semiconductor Solutions and Japanese automotive components maker Denso Corporation to fuel the growth of the country’s semiconductor ecosystem.
Japan has been striving to strengthen its semiconductor presence amid an intense rivalry with key chip making countries such as Taiwan and South Korea. Its chip-manufacturing industry is 10 years behind world leaders TSMC and Samsung, according to an August report from the Center For Strategic & International Studies.
Earlier this month, TSMC, Sony Semiconductor Solutions, automaker Toyota and Denso announced further investment into JASM to build a second chip fabrication plant, with construction set to start by year-end and operations to commence by end-2027.
With the two plants, which are expected to directly create more than 3,400 high-tech professional jobs, the Japanese government’s investment into JASM will total more than $20 billion.
TSMC’s two factories in Japan will focus on producing semiconductors for automotive, industrial, consumer uses and to meet high-performance computing-related needs.
The company is also building one of its largest overseas projects with a $40 billion investment in Arizona for two chip manufacturing plants aimed at meeting the U.S. annual demand.
Jensen Huang, chief executive officer of Nvidia Corp., during the US-Saudi Investment Forum at the Kennedy Center in Washington, DC, US, on Wednesday, Nov. 19, 2025.
Stefani Reynolds | Bloomberg | Getty Images
In the weeks leading up to Nvidia’s third-quarter earnings report, investors debated whether the markets were in an AI bubble, fretting over the massive sums being committed to building data centers and whether they could provide a long-term return on investment.
During Wednesday’s earnings call with analysts, Nvidia CEO Jensen Huang began his comments by rejecting that premise.
“There’s been a lot of talk about an AI bubble,” Huang said. “From our vantage point we see something very different.”
In many respects, Huang’s remarks are to be expected. He’s leading the company at the heart of the artificial intelligence boom, and has built its market cap to $4.5 trillion because of soaring demand for Nvidia’s graphics processing units.
Huang’s smackdown of bubble talk matters because Nvidia counts every major cloud provider — Amazon, Microsoft, Google, and Oracle — as a customer. Most of the major AI model developers, including OpenAI, Anthropic, xAI and Meta, are also big buyers of Nvidia GPUs.
Huang has deep visibility into the market, and on the call he offered a three-pronged argument for why we’re not in a bubble.
First, he said that areas like data processing, ad recommendations, search systems, and engineering, are turning to GPUs because they need the AI. That means older computing infrastructure based around the central processor will transition to new systems running on Nvidia’s chips.
Second, Huang said, AI isn’t just being integrated into current applications, but it will enable entirely new ones.
Finally, according to Huang, “agentic AI,” or applications that can run without significant input from the user, will be able to reason and plan, and will require even more computing power.
In making the case of Nvidia, Huang said it’s the only company that can address the three use cases.
“As you consider infrastructure investments, consider these three fundamental dynamics,” Huang said. “Each will contribute to infrastructure growth in the coming years.”
Reversing the slide
In its earnings release, Nvidia reported revenue and profit that sailed past estimates and issued better-than-expected guidance. Last month, Huang provided a $500 billion forecast for sales of the company’s AI chips over calendar 2025 and 2026.
The company said on Wednesday that its order backlog didn’t even include a few recent deals, like an agreement with Anthropic that was announced this week or the expansion of a deal with Saudi Arabia.
“The number will grow,” CFO Colette Kress said on the call, saying the company was on track to hit the forecast.
Prior to Wednesday’s results, Nvidia shares were down about 8% this month. Other stocks tied to the AI have gotten hit even harder, with CoreWeave plunging 44% in November, Oracle dropping 14% and Palantir falling 17%.
Some of the worry on Wall Street has been tied to the debt that certain companies have used to finance their infrastructure buildouts.
“Our customers’ financing is up to them,” Huang said.
Specific to Nvidia, investors have raised concerns in recent weeks about how much of the company’s sales were going to a small number of hyperscalers.
Last month, Microsoft, Meta, Amazon and Alphabet all lifted their forecasts for capital expenditures due to their AI buildouts, and now collectively expect to spend more than $380 billion this year.
Huang said that even without a new business model, Nvidia’s chips boost hyperscaler revenue, because they power recommendation systems for short videos, books, and ads.
People will soon start appreciating what’s happening underneath the surface of the AI boom, Huang said, versus “the simplistic view of what’s happening to capex and investment.”
WATCH: Nvidia posts Q3 beat
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