Nvidia Server Maker Wiwynn Sees AI Bottlenecks Beyond Memory

Yahoo Finance · 2026-05-28

Nvidia Server Maker Wiwynn Sees AI Bottlenecks Beyond Memory 1 / 2 Nvidia Server Maker Wiwynn Sees AI Bottlenecks Beyond Memory Debby Wu and Miaojung Lin Thu, May 28, 2026 at 3:58 AM CDT 2 min read 6669.TW NVDA META 2382.TW 2317.TW (Bloomberg) -- Wiwynn Corp., one of the biggest makers of Nvidia Corp. servers, warned of shortages developing in vital data center components beyond just memory chips, potentially slowing or inflating the cost of a global AI infrastructure buildout. Singapore Hands Byju's Founder His First Ever Jail Term Iran’s Khamenei Says No Going Back for Middle East Rocked by War Ex-President Biden Sues to Stop DOJ Sharing Interview Tapes Two More Oil Supertankers Exit Hormuz to Help Push Up Flows ‘KPop Demon Hunters’ Studio Draws Tencent Music Investment Wiwynn Chair Emily Hong expects demand for data center hardware to remain red-hot over the next three to five years, as the likes of Meta Platforms Inc. and Microsoft Corp. escalate capital spending. But that race to secure essential components from memory to networking chips is propelling hardware prices to record highs. It’s hard to pin down where crunches will emerge, given a constant race to expand production capacity. “The items that are in short supply are somewhat different every year,” Hong told Bloomberg News on Thursday. “We may start to see some relief in constraints in late 2027 or 2028.” Hong joins fellow industry figures in warning about demand-supply imbalances. The executive, whose firm competes with Hon Hai Precision Industry Co. and Quanta Computer Inc., often joins what’s dubbed “The Trillion Dollar Banquet:” a regular dinner hosted by Nvidia boss Jensen Huang when he visits his Taiwanese partners. Wiwynn is now generating over 80% of its sales from US customers, Hong said. America will be a key location for expansion over the next few years, though she did not provide a specific number for investment. Wiwynn’s first plant in El Paso, Texas is already up and running, and it’s planning to ready another three in two years’ time, the executive said. The company has been able to secure sufficient power supply, which is critical for assembling AI server racks in the Lone Star state, she added. The Taiwanese company is currently exploring ways to raise capital for expansion - not just in the US but also back home. Hong, who spoke with Bloomberg News during a joint interview with Taiwan Stock Exchange Chairman Sherman Lin, said the $2 billion of convertible bonds the company issued this March won’t cover its capex requirements over the next several years. She said WiWynn may try to raise more funds next year, primarily utilizing global depositary receipts and convertible bonds. (Updates with Hong’s comments on funding in the seventh paragraph.) It’s Such a Mess Shopping for Reasonably Priced Menswear How Barnes & Noble Became Private Equity’s Most Radical Retail Experiment

AI 시장 분석

Nvidia server maker Wiwynn warns of bottlenecks and rising prices for critical data center components beyond memory, essential for AI infrastructure buildout. While demand from major players like Meta and Microsoft remains strong, component shortages could slow down deployment or increase costs. Wiwynn is seeking to raise capital for its expansion in the US.

상승 영향

AI Server Manufacturers — AI infrastructure buildout demand is expected to remain red-hot for 3-5 years, leading to increased sales for AI server manufacturers like Wiwynn.
Data Center Infrastructure — Escalating AI investments and infrastructure buildout by major companies will continuously drive demand for data center-related hardware and services.
Semiconductors — Demand for AI data center semiconductors, including memory and networking chips, is surging, driving up prices and improving profitability.
Power Infrastructure — The critical importance of securing power supply for AI server rack assembly is highlighted, increasing demand for power infrastructure investment due to data center expansion.

하락 영향

AI Adopters — Bottlenecks in critical components and rising hardware prices for AI infrastructure will increase initial investment costs and slow down the adoption pace for AI technology adopters.
Cloud Service Providers — Increased AI infrastructure buildout costs and component supply uncertainties may raise operating expenses for cloud service providers and limit service expansion.

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