- New Samsung AI Megafactory merges chipmaking, robotics, and digital twins into one networked ecosystem
- The company integrates Nvidia Omniverse to simulate and optimize complex factory operations
- AI-managed lithography promises faster production cycles and sharper wafer pattern precision
Samsung has announced plans to build what it calls an “AI Megafactory,” powered by over 50,000 Nvidia GPUs and the Nvidia Omniverse platform.
The project aims to embed AI intelligence throughout its semiconductor, mobile, and robotics operations.
This would set the stage for what could become a global benchmark in intelligent manufacturing and transform its semiconductor and robotics production.
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Expanding AI into semiconductor design and production
Samsung’s goal is to use AI to connect design, manage processes, operate equipment, and ensure quality control within a unified digital system.
Using Nvidia’s cuLitho and CUDA-X libraries, the company claims a 20-fold improvement in computational lithography.
These gains suggest shorter development cycles and more efficient fabrication are achieved through a process essential for producing accurate wafer patterns.
However, questions remain about the long-term stability and maintenance of such AI-reliant systems.
The company is also collaborating with partners in electronic design automation to develop GPU-accelerated EDA tools that could redefine chip design efficiency.
Samsung will use Nvidia Omniverse libraries to create digital twins of its fabrication plants, simulating factory operations to identify faults and optimize performance before real-world deployment.
While this approach may improve efficiency, it also increases Samsung’s reliance on cloud hosting and web hosting for data processing and visualization.
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It also increases its dependence on AI-driven design, which raises issues of oversight, reproducibility, and the potential for technical lock-in within Nvidia’s ecosystem.
Samsung is also extending its AI infrastructure into robotics, applying Nvidia RTX PRO 6000 Blackwell Server Edition systems and the Jetson Thor platform.
These technologies aim to enhance automation and autonomy in both humanoid and industrial robots.
They promise greater precision and adaptability and reflect an industry trend toward merging physical and digital intelligence under centralized platforms.
Samsung and Nvidia’s collaboration extends over 25 years, evolving from memory supply for early graphics cards to joint development of next-gen HBM4 memory.
The new AI Megafactory appears to strengthen that relationship, but the consolidation of advanced AI tools within a few dominant tech alliances raises broader concerns.
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