As the next chapter of AI takes the world by storm, leading tech companies are prepping their latest platforms while working simultaneously with partners to ensure a steady supply to meet their targets.

Today, AMD announces its readiness to cater to this growing AI demand by pooling in over $10 billion worth of investments towards the Taiwan ecosystem and its regional partners who will soon be supplying one of the fastest AI Racks on the market to date, codenamed Helios. This powerful rack, designed purely for AI, houses the company's latest 6th Gen EPYC CPUs codenamed Venice, and the Instinct MI450X AI GPUs.

More than $10 billion in investments across the Taiwan ecosystem to expand strategic partnerships and scale advanced packaging capabilities for AI infrastructure Industry-leading EFB-based 2.5D packaging to enable higher interconnect bandwidth and efficiency in 6th Gen AMD EPYC CPUs, codenamed “Venice.” AMD Helios rack-scale platform with “Venice” and AMD Instinct MI450X GPUs on track for multi-gigawatt deployments beginning 2H 2026 AMD is working with various "strategic" Taiwanese partners, which include ODMs such as Sanmina, Wiwynn, Wistron, and Inventec, alongside SPIL, PTI, Unimicron, AIC, Nan Ya PCB, and Kinsus, who will be building & shipping the latest Helios AI Racks, setting the stage for its Agentic AI roadmap.

Press Release: To meet the growing demand for AI infrastructure, AMD today announced more than $10 billion in investments across the Taiwan ecosystem to expand strategic partnerships and scale advanced packaging manufacturing for next-generation AI infrastructure.

Working with strategic partners in Taiwan and globally, AMD is advancing leading-edge silicon, packaging, and manufacturing technologies that enable higher performance, greater efficiency, and faster deployment of AI systems. These efforts build on AMD’s deep ecosystem partnerships and long-standing leadership in chiplet architectures, high-bandwidth memory integration, 3D hybrid bonding, and rack-scale system design for next-generation AI infrastructure.

By: DocMemory
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