Why Is the AI Hardware Race Splitting Into Two Tracks and Why Taiwan Matters?

Q1. What is driving the shift from a GPU-only boom to a dual GPU and ASIC race?
Demand for custom AI chips has accelerated as hyperscalers push for efficiency and scale. Hon Hai is producing over 1,000 AI racks per week for TPU deployments and plans to double output by 2026. Analysts expect high-end ASIC shipments to grow 41 percent annually. This signals a new phase in AI infrastructure where diversified hardware suppliers become the more resilient winners.

Q2. How is Taiwan consolidating its upstream position in advanced materials and semiconductor manufacturing?
A new 500 million Euro materials mega site in Kaohsiung will produce thin-film solutions and specialty gases essential for advanced nodes. Executives say the site can meet about 80 percent of Taiwan’s thin-film needs. This local-for-local strategy reduces logistics risk, strengthens resilience, and deepens Taiwan’s integration into the global AI supply chain.

Q3. Why is Southeast Asia emerging as a new strategic front in AI infrastructure?
Major AI builders are expanding their data center footprints across Singapore, Malaysia, Thailand, and Vietnam. This shift is driving demand for server chassis and racks that must be produced regionally. Taiwanese manufacturers such as Chenbro, Wistron’s network, and JPP-KY are scaling capacity in the region. This positions them to capture the next wave of AI-driven buildouts.

Follow the podcast for the full analysis from Taiwan’s vantage point.

What Are Taiwan’s Latest AI Signals Telling Us About the Next Tech Cycle?

From Taipei, we track the signals shaping the world’s most valuable supply chain. Taiwan just raised its 2025 GDP forecast to 7.37 percent on the strength of AI server demand, yet manufacturing indicators slipped into a caution zone and markets pulled back as investors took profits. The question is how these mixed signals should be read as the next tech cycle forms.

Q1. Are we seeing acceleration or early caution?

GDP revisions reflect a powerful AI hardware surge, driven by U.S. cloud giants expanding capacity. At the same time, October manufacturing data turned yellow blue and the TAIEX fell more than 1 percent after a rapid AI rally. The long term trajectory is strong, but near term sentiment is cautious.

Q2. What do U.S. tariff talks reveal about supply chain strategy?

Negotiations on Section 232 steel and aluminum duties aim to prevent tariff stacking and align Taiwan with Japan’s 15 percent rate. With TSMC investing 40 billion dollars in Arizona, a clearer framework signals deeper cooperation in securing semiconductor resilience.

Q3. Why is the HBM race intensifying?

Micron announced a 9.6 billion dollar HBM project in Japan. DigiTimes reports Nvidia is expanding from SK Hynix to Samsung for upcoming HBM4. The demand is driven by enterprise scale AI adoption, reinforced by new partnerships such as OpenAI and Accenture.

Q4. How is MediaTek navigating the next frontier?

The company is moving from fast follower to original AI chip designer. It has scaled its AI division to several thousand engineers and is investing in new capabilities like advanced packaging and silicon photonics. Its reinvention illustrates how the next cycle will reward companies that can innovate at zero to one speed.

Can the World Build AI Fast Enough When Taiwan’s Supply Chain Is Already at Full Stretch?

Q1: Why is global AI demand hitting physical limits so quickly?
Because the build out is happening faster than infrastructure can keep up. Tech giants may spend up to 320 billion dollars on AI data centers in 2025, but Bloomberg reports the U.S. grid could face a power shortfall by 2028. The AI boom is outpacing electricity, land, and construction timelines.

Q2: What does Taiwan’s newest bottleneck tell us about the AI supply chain?
GPTC, a key CoWoS equipment supplier, can meet only about half of customer demand even as its revenue rises 53 percent. Since TSMC anchors global advanced packaging, any shortage in upstream tools or capacity in Taiwan becomes a system wide constraint. The pace of global AI expansion depends on Taiwan’s floorspace, equipment, and engineering talent.

Q3: How are companies adapting as AI reshapes cost structures and competition?
HP is cutting up to 6,000 jobs and reinvesting 1 billion dollars in AI automation. Amazon is expanding its strategy of offering multiple AI models as building blocks rather than locking customers into one ecosystem. AWS positions itself as the platform layer, while Google and Meta explore custom chips to manage cost. The market is not shrinking. It is reorganizing around efficiency, openness, and platform scale.

Why Is the Future of the World’s AI Chips Being Decided in Taiwan?

Why does the U.S. need Taiwan’s semiconductor expertise now more than ever?
Because Washington cannot fix its talent gap alone. Reuters reports the U.S. is negotiating a deal that lowers Taiwan’s 20 percent export tariff in exchange for Taiwanese investment and on-the-ground engineering support. TSMC would send teams to train American workers, addressing the labor shortage C. C. Wei highlighted when he said Arizona’s fab took twice as long to build as one in Taiwan. Capital can build fabs, but only Taiwan can supply the deep know-how needed to run them.

Is Meta’s potential shift to Google TPUs a real challenge to Nvidia’s dominance?
It signals pressure, not a power shift. Taiwan’s CNA says Meta will test Google TPUs next year and consider adoption by 2027. Nvidia’s moat remains CUDA, the ecosystem developers rely on. But rising costs are pushing experimentation. Pegatron chairman Tung Tzu-hsien notes that no matter who designs the chip, the manufacturing still ends up at TSMC. Competition may intensify, but Taiwan stays at the center of advanced AI hardware.

Are we in an AI bubble or entering a decade-long AI super cycle?
Industry leaders say the growth is real. Foxconn CEO Yang Chiu-chin points to more than 600 billion dollars already invested by global cloud providers and over 4.4 billion in expected AI data center spend in 2025. Foxconn itself is investing 1.4 billion in Taiwan and expanding partnerships with Nvidia and Stellantis. Venture investors also view demand as structural, not speculative. With Taiwan anchoring the manufacturing base, the cycle is only beginning.

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Meta x Google: The Next AI Chip Shift and Taiwan’s Upside

Q1. What is the larger strategic signal behind Meta exploring Google’s TPUs
Meta is in advanced discussions to use Google’s TPUs, according to The Information and Reuters. The plan includes renting TPUs through Google Cloud next year and evaluating Google’s custom chips for Meta’s data centers around 2027. Meta’s AI budget could reach 72 billion dollars this year, creating significant room for alternatives to Nvidia. Analysts cited by CNBC say Google aims to capture about 10 percent of Nvidia’s annual revenue through a fully integrated model that includes Gemini, Google Cloud and TPUs. Alphabet’s stock rose more than 4 percent following the reports. The deeper message is clear. The AI hardware market is beginning to decentralize, reducing reliance on a single supplier and opening a new phase of competitive chip innovation.

Q2. Where is Taiwan positioned as this new landscape forms
Taiwan remains the center of gravity. Advanced packaging is becoming a defining bottleneck, and Taiwan leads this domain through TSMC and ASE. Media reports say ASE is investing NT 4.23 billion, roughly 134 million U.S. dollars, to acquire a new facility in Taoyuan and co develop another in Kaohsiung. These moves expand CoWoS capacity, which is essential for the AI accelerators that companies like Meta and Google now seek. Industry sources expect AI related CoWoS demand to continue through 2027. TSMC’s packaging lines are reportedly booked through 2026, underscoring how tightly constrained and strategically important Taiwan’s capacity has become.

Why Taiwan Is Becoming the Strategic Center of the Global Chip Fight

Q1. What new signals suggest a shift in US semiconductor policy toward China?
A potential rule change reported by Reuters shows the US Commerce Department is considering allowing Nvidia to sell its H200 AI chips to China. The H200 carries more high-bandwidth memory and roughly twice the performance of the restricted H20 model. This could reopen one of Nvidia’s largest global markets.  If approved, the decision suggests a recalibration in Washington as it balances economic competitiveness with national security priorities. This shift will influence how global chipmakers plan their long-term China strategies.

Q2. Why is Nvidia expanding deeper into Taiwan at the same time?
While US export rules evolve, Nvidia is accelerating its physical presence in Taiwan. The Taipei City government has cleared land-use contracts in the Beitou Shilin Technology Park for Nvidia’s new headquarters. Construction could start in 2026. The facility will serve as an R&D and coordination hub, reinforcing why global AI companies continue to anchor mission-critical operations in Taiwan’s manufacturing and engineering ecosystem.

Q3. How are other Asian governments responding to this strategic moment?
Japan is making one of its largest public investments in decades. According to CommonWealth Magazine English Website, Tokyo is adding 6.4 billion USD in funding to Rapidus, pushing total support above 50 billion USD. The goal is to mass-produce 2-nanometer chips by 2027 and move toward 1.4-nanometer nodes. This signals Japan’s intent to re-establish itself as a meaningful advanced-process player and diversify global manufacturing capacity beyond its current concentration.
About the Show

Below is today’s snapshot of the Foxconn and Nvidia story redefining the boundaries of the AI economy.

Q1. Why is Foxconn moving from assembly to architecture in the AI era

Foxconn is positioning itself as a full stack AI infrastructure builder. At its latest Tech Day, the company announced a Taiwan based AI data center that will deploy Nvidia’s GB300 NVL72 platform, described by Focus Taiwan as one of the most powerful AI systems globally. The 27 megawatt facility is expected in 2026 and is framed as a foundation for sovereign AI, enabling Taiwan’s 1.6 million small and medium sized businesses to access domestic compute capacity.
Foxconn’s partnerships with OpenAI and Alphabet’s Intrinsic extend this shift beyond Taiwan. Sam Altman noted that demand for critical AI infrastructure components is already far outpacing supply, underscoring Foxconn’s role in relieving bottlenecks.
Takeaway: This is a deliberate pivot into long term value creation. The strategy reframes Foxconn from a contract manufacturer into a global AI infrastructure architect.

Q2. What does Nvidia’s deeper presence in Taiwan signal about the global supply chain

Nvidia has secured approval from Taiwan’s Ministry of Economic Affairs to establish a formal subsidiary, supported by a 32 million US dollar investment. Taipei’s mayor confirmed that Nvidia plans to build a new Taiwan headquarters in the Beitou Shilin Technology Park.
Until now, Nvidia operated through Hong Kong based units. A local subsidiary enables direct asset ownership, streamlined R&D funding, and tighter integration with suppliers.
Takeaway: Nvidia’s move locks in long term proximity to the world’s most advanced semiconductor ecosystem, reinforcing Taiwan’s central role in the global AI hardware cycle.

Q3. Are current AI investments pushing the market toward a correction

Semiconductor stocks dropped sharply across Asia, with Taiwan’s Taiex down 3.4 percent and TSMC and Foxconn both falling more than 4 percent. In Korea, Samsung and SK Hynix slid as much as 6 and 10 percent. Dow Jones Newswires noted renewed concerns about an AI bubble. A Bank of America survey shows that 53 percent of institutional investors already view AI valuations as bubble territory.
Meanwhile, resource constraints add pressure. A Verge investigation highlights water and power challenges in Arizona, where TSMC’s first fab is projected to consume 4.75 million gallons of water per day, with up to 16 million gallons across three fabs. TSMC aims to recycle 90 percent of its water by 2028, but shortages remain a structural risk.
Takeaway: Markets are signaling caution as financial and environmental constraints collide with aggressive AI infrastructure expansion.

Listen to the full episode for the complete breakdown.

The Rise of Agentic AI and the New Silicon Power Map Anchored in Taiwan

Q: Why did one earnings report move markets from Wall Street to Taipei?
Nvidia reported 51.2 billion dollars in Q3 data center revenue, beating expectations and guiding for mid-sixties next quarter. Jensen Huang said early Blackwell demand is “off the charts”. Taiwan felt the impact immediately. The Taiex surged 846 points, a 3.18 percent jump. TSMC rallied 4.3 percent. Foreign investors added 13.11 billion NT dollars, according to Focus Taiwan. The surge signals how tightly Taiwan’s economy is linked to global AI infrastructure demand.

Q: What does this mean for Taiwan’s role?
Google opened its largest AI hardware infrastructure engineering center outside the United States in Taipei. President Lai said the move shows Taiwan is both a vital part of the global supply chain and a key hub for secure and trustworthy AI. Google Cloud leadership highlighted Taiwan’s engineering depth and its ability to shorten hardware development cycles. Equipment designed in Taipei will be deployed in Google data centers worldwide.

Q: What protections and standards does the AI boom demand?
The @European Chamber of Commerce Taiwan urged the government to pass a comprehensive AI Basic Act. It highlighted the need for human-centered safeguards and intellectual property protection. As AI deployment accelerates, regulation becomes part of supply chain resilience.

Across markets, geopolitics, hardware engineering, and energy systems, the same pattern is emerging. Taiwan is positioned at the center of a global AI realignment that is only beginning. The next phase of the AI boom will reward leaders who understand how semiconductor capacity, power grids, policy, and capital flows intersect. Inside Taiwan tracks these signals every day.

Today’s episode examines three questions shaping the next phase of Taiwan’s tech future, from advanced process IP to energy security to the trillion-dollar AI investment curve.

Q1: Why is Taiwan treating the TSMC investigation as a national security moment
A former senior VP for corporate strategy at TSMC, Lo Wei jen, is under investigation after allegedly removing restricted documents tied to the 2 nanometer node and the upcoming A16 and A14 roadmaps for 2026 and 2028. Focus Taiwan reports he took more than 80 boxes of materials before returning to Intel after 21 years at TSMC. Prosecutors and the Ministry of Economic Affairs are evaluating potential violations of national security law.

This case underscores the vulnerability of advanced node IP at a time when months of advantage translate into global market power. The concern is not only commercial. It is geopolitical. Taiwan’s process leadership is the anchor of the global AI hardware economy, and this incident shows how fragile that moat can be when talent mobility collides with strategic technology.

Q2: What is the largest constraint on Taiwan’s AI ambitions according to industry leaders
Former Intel CEO Pat Gelsinger delivered a stark warning in Taipei. As reported by the Taipei Times, he stated that Taiwan is not in a position to secure a resilient energy supply chain and that energy reliability is the single biggest obstacle to AI growth. Semiconductor manufacturing already consumes about 10 percent of Taiwan’s electricity according to DIGITIMES Asia.

Gelsinger noted that this energy ceiling is the reason the AI boom is not a classic bubble. Cloud companies cannot deploy infrastructure faster than the grid can support it. He also pointed to new technologies like xLight’s EUV alternative, which aims to double lithography productivity while cutting power use. These innovations highlight both the urgency and opportunity of Taiwan’s next wave of industrial upgrades.

Q3: Is the global AI boom a sustainable cycle or a bubble with structural limits
Google CEO Sundar Pichai told the BBC that AI investment contains irrational elements, even as he argues the underlying shift is profound. Google has tripled its annual infrastructure spending from 30 billion dollars to more than 90 billion dollars, with industry-wide investment surpassing the trillion-dollar mark.

Real-world ripple effects are already emerging. Reuters cites Counterpoint Research reporting that Nvidia plans to shift server memory from DDR5 to LPDDR to reduce energy consumption. This change will tighten supply across memory categories and push server memory prices up, with forecasts of potential doubling by late 2026. These shifts illustrate the physical constraints and supply chain interdependencies that shape whether AI growth accelerates or stalls.

Q4: How is Taiwan responding as global competition intensifies
Taiwan News reports that the government has launched a NT 100 billion program, approximately 3.2 billion US dollars, to position the island as a global AI hub. The investment aims to generate NT 15 trillion in economic value by 2040 and includes new research centers in silicon photonics and quantum computing, along with a national AI computing facility.

Yet the same energy bottleneck that Gelsinger highlighted remains the pivotal variable. Taiwan is committing to an AI industrial future, but the scale of its ambition demands energy resilience that has not yet been secured.
Listen to the full episode
Inside Taiwan unpacks what these tensions reveal about the next decade of semiconductor leadership and the realities shaping the global AI economy.

【About the Show】Inside Taiwan distills 200 stories a day from over 30 trusted Traditional Chinese and English sources into a ten minute executive briefing. It is an AI powered signal over noise for global investors and decision makers navigating the world’s most valuable supply chain.

From Taipei, the center of the world’s semiconductor engine, we track the key shifts shaping the global AI supply chain. Inside Taiwan is a daily AI-powered podcast delivering fast, reliable analysis from the island’s unique vantage point.

Q: Is the AI market cooling, or is demand still accelerating beneath the volatility?
Institutional selling from major investors contrasts with record-high demand across compute infrastructure. Taiwan’s supply chain data, from TSMC’s reserved 3 nanometer capacity to double-digit AI server growth forecasts, suggests long-term acceleration rather than a slowdown.

Q: What bottlenecks could slow the next phase of AI growth?
Energy supply remains a significant constraint for the island, and semiconductor capacity limits are emerging as global choke points. These pressures mirror the concerns raised by leaders like Satya Nadella and Andrew Ng, who see supply constraints rather than demand risks.

Q: Which technologies signal where the next breakthroughs will come from?
Silicon photonics is gaining momentum as companies shift from copper to light, improving speed and energy efficiency. New Taiwan-linked partnerships, including Ayar Labs and GUC working toward mass production by 2028, point to an inflection in next-generation AI architecture.

Q: Why is learning to code with AI becoming a core skill for the future?
Andrew Ng argues that the belief that “coding is obsolete” is deeply misleading. AI lowers the barrier to software creation, but people still need to frame problems clearly and tell computers exactly what to do, which makes coding with AI more important, not less.
Listen to the full episode for the complete breakdown of the signals shaping the world’s most valuable supply chain.

【About the Show】Inside Taiwan distills 200 stories a day from over 30 trusted Traditional Chinese and English sources into a ten-minute executive briefing. It is an AI-powered signal over noise for global investors and decision-makers navigating the world’s most valuable supply chain.