Foxconn and NVIDIA to Build AI Supercomputer in Taiwan
Foxconn, through its subsidiary Big Innovation Company, is partnering with NVIDIA and the Taiwan government to build an AI supercomputer featuring 10,000 NVIDIA Blackwell GPUs, announced in a press release. This AI factory aims to enhance AI computing capabilities for researchers, startups, and industries across Taiwan.
The Taiwan National Science and Technology Council will invest in this supercomputer to accelerate AI development and adoption across various sectors. The infrastructure will also support TSMC's research and development efforts, providing significantly faster performance compared to previous systems.
The AI factory will be equipped with NVIDIA Blackwell Ultra systems, including the NVIDIA GB300 NVL72 rack-scale solution. It will also participate in the NVIDIA DGX Cloud Lepton marketplace, offering advanced GPU resources to a wide range of enterprises, from startups to established industry leaders.
Foxconn plans to leverage the AI supercomputer to enhance automation and efficiency in smart cities, electric vehicles, and manufacturing, aiming to connect industries, citizens, and government organizations to drive growth with AI.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.
Also, consider following us on social media:
More from Data Centers
Sep 30 Sophia Space and Redwire Explore Orbital Data Centers Sep 30 SKF Recreates Greta Garbo With AI for Magnetic Bearing Campaign Sep 30 LG Innotek Targets $5.94 Billion in Semiconductor and Physical AI Businesses Sep 29 Efficient Computer Raises $97 Million to Scale Its Processors Sep 29 Hikvision Adds HIKO AI Engine to Hik-Connect 7Silicon Brief
Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Compal to Show NVIDIA AI Factory Infrastructure at OCP Summit
Nscale Secures $3 Billion for AI Campuses in Texas and North Carolina
Delta Develops Power and Cooling Infrastructure for NVIDIA DSX AI Factories
ASUS Shows ProArt RTX Spark PCs at IFA 2026
Acer Shows Compact RTX Spark Desktop Design at IFA 2026
Daily AI Brief: the AI news that matters, in your inbox.