NVIDIA & SK Hynix’s Technology Partnership for AI Factories

The world's largest company by market cap, NVIDIA, and South Korean manufacturer SK Hynix announced a multiyear technology partnership to advance 'next-generation' memory for the global AI factory buildout and accelerate semiconductor design and manufacturing.

The agreement supports supply for advanced memory, addressing the extended development cycles, advanced fabrication and capital investments to sustain the global buildout of AI factories.

In April of 2026, the Financial Times reported that SK Hynix plans to significantly increase its capital spending this year in response to long-term demand growth as big tech companies spend hundreds of billions of dollars on AI hardware.

AI factories and advanced memory

Jensen Huang, founder and CEO of NVIDIA, says: “AI factories are the engines of the next industrial revolution and advanced memory is essential to their performance.

“SK Hynix has been an extraordinary partner to NVIDIA, playing a central role in delivering advanced memory technologies for NVIDIA AI computing platforms. 

“Together, we will co-develop the next generation of memory for AI factories and support the accelerating global expansion of AI infrastructure, from frontier model training to agentic and physical AI.”

As part of the deal SK Hynix will diversify into new markets NVIDIA is creating across AI infrastructure, personal AI and physical AI, co-developing memory for NVIDIA Vera Rubin AI supercomputers, Vera CPUs, RTX Spark-powered PCs and Jetson Thor robotic computing platforms.

AI for manufacturing semiconductors

In a press release, NVIDIA says that the two companies will apply AI to semiconductor chip design and manufacturing, using NVIDIA CUDA-X libraries and NVIDIA PhysicsNeMo to accelerate semiconductor simulations, TCAD workflows and in-house engineering codes.

Chey Tae-won, Chairman of SK Group, says: “SK Hynix and NVIDIA have been building toward this for years, and this partnership reflects the depth of that collaboration.

“Together, we are co-developing the next generation of memory for AI factories and applying AI to how we design and manufacture semiconductors — work that will shape the future of AI infrastructure.”

SK Hynix uses NVIDIA's framework and libraries to speed semiconductor simulation, including technology computer-aided design and computational lithography workflows, and to deliver core-workload acceleration across its in-house simulation codes and AI physics workflows.

SK Hynix and NVIDIA's digital twins

SK Hynix is ​​developing fab digital twins as a foundation for autonomous fab operations. Its teams can use scene optimisation technologies, as well as NVIDIA Omniverse libraries and OpenUSD pipelines, to build 3D factory scenes for visualising, simulating and optimising complex semiconductor manufacturing environments.

These digital twins can also support operational optimisation, including the movement of autonomous mobile robots and other fab assets, using the open source, GPU-accelerated NVIDIA cuOpt decision optimisation engine and the NVIDIA Metropolis platform.

NVIDIA's agreement's with SK Telecom and Doosan

NVIDIA also announced an agreement with SK Telecom, which like SK Hynix is ​​part of the SK Group, that spans factory architecture to accelerate AI startup's, robotics and industrial physical AI. 

SK Telecom plans to build a gigawatt-scale AI Cloud in Korea using the NVIDIA DSX platform, with the first AI factory planned to come online in 2027. 

Jensen said about the agreement with SK Telecom: “Telecom networks are becoming national AI infrastructure.

“They connect people, companies, devices and machines and now they can become the backbone of new AI clouds. 

“With NVIDIA DSX, SK Telecom can build Korea's AI cloud at scale and bring agents, enterprise and physical AI to the companies and industries that power Korea and the world.”

Additionally, NVIDIA signed a deal with another South Korean company, Doosan Group , expanding collaborations across physical AI, robotics and AI factory infrastructure.