The Nvidia Samsung AI partnership is redefining how semiconductor manufacturing will operate in the coming years. Samsung plans to build an AI-driven production environment that uses more than 50,000 Nvidia GPUs. Because of this scale, the project could become one of the most advanced digital manufacturing systems ever deployed. It also marks a major step in Samsung’s broader digital transformation.
Nvidia CEO Jensen Huang says the industry is entering “the dawn of the AI industrial revolution.” According to him, Samsung wants to lead this shift by creating a smarter, more autonomous approach to chip manufacturing.
How the Nvidia Samsung AI partnership reshapes semiconductor manufacturing
Samsung plans to combine Nvidia GPUs with Nvidia CUDA-X, along with tools from Synopsys, Cadence and Siemens. This mix allows faster circuit simulation, quicker verification and more accurate manufacturing analysis. As a result, engineers can catch problems earlier and move through the production cycle with far less friction.
The companies have worked together for decades. Samsung Chairman Jay Y. Lee says this new AI factory continues their shared history. He also adds that Samsung intends to set new standards for future manufacturing and accelerate global innovation through this project.
Samsung’s new facility will also use a real-time digital twin. This technology mirrors every action inside the factory. Therefore, teams can simulate production steps, adjust workflows, detect anomalies and optimise logistics without slowing real operations. It may also reduce environmental impact by identifying inefficient processes early.
Samsung and Nvidia claim the combined system can deliver up to 20× better performance across key stages of semiconductor manufacturing. Because the platform scales easily, Samsung can apply these improvements across many production lines.
How the Nvidia Samsung AI partnership tackles sustainability challenges in AI factories
As AI adoption expands, industries are paying more attention to energy consumption. Data centres already demand a large share of global electricity. Jensen Huang notes that this trend cannot continue without new solutions that protect both budgets and the environment.
To respond, Nvidia created the GB300 NVL72 platform. It includes energy-storage features and intelligent power-management tools. These components limit peak loads during heavy AI tasks and reduce pressure on local grids. As a result, companies can train and operate AI models more efficiently.
Nvidia’s broader view: AI as a tool for sustainability
Nvidia believes AI can do more than optimise its own hardware. According to Josh Parker, Nvidia’s Senior Director of Corporate Sustainability, AI could become one of the best tools for improving long-term sustainability.
He explains that accelerated computing — which combines GPUs and CPUs for complex workloads — delivers major efficiency gains. Nvidia states that accelerated systems can be up to 20× more energy-efficient than traditional CPU-only clusters. Parker adds that efficiency for AI inference has improved 45,000× in eight years, showing how fast the industry is progressing.
In March 2026, Parker will join a panel on AI and sustainability at Sustainability LIVE: The Net Zero Summit. He will discuss how AI can support emissions tracking, energy optimisation, climate modelling and more responsible supply-chain management.
Conclusion
The Nvidia Samsung AI partnership shows how AI can reshape semiconductor manufacturing from the ground up. Samsung plans to rely on Nvidia’s accelerated computing ecosystem to build smarter factories, improve performance and reduce environmental impact. This collaboration may set a new benchmark for intelligent, efficient and sustainable industrial operations.
Read also
Join the discussion in our Facebook community.