On June 5th, the South Korean stock market experienced a “Black Friday,” with the KOSPI index plummeting 5.54% at the close. After the market opened on June 8th, intraday losses expanded to over 8%, triggering a circuit breaker mechanism. Both Samsung and SK Hynix fell by nearly 10%. Amidst a climate of fear in the market, Jensen Huang’s visit dramatically took on the role of “market savior.”
Previously, on the evening of Sunday, June 7th, local time in South Korea, Jensen Huang held a “dinner meeting” with SK Group Chairman Chey Tae-won, SK Hynix CEO Kwak Noh-jung, and others. After the meal, Huang confirmed to the media present: NVIDIA’s newly launched Vera CPU will use SK Hynix DRAM; the two sides are preparing for “large-scale cooperation” in the second half of this year and next year; regarding the current shortage of memory chips, he believes it will continue for several years. Subsequently, NVIDIA and SK Hynix officially announced a multi-year technology cooperation agreement, covering everything from AI supercomputers to robotics, digital twins, and semiconductor manufacturing. Jensen Huang even directly promoted the stocks at a press conference, saying, “If you are a shareholder of an AI company, you will be happy, as their prices are very low right now.”
01 Locking in SK Hynix Memory
Vera is NVIDIA’s first independent CPU specifically for data centers, facing competitors such as Intel’s Xeon product line, AMD’s Epyc chips, and self-developed projects by large cloud service providers like Amazon’s Graviton. In this new battlefield, NVIDIA has anchored its memory supply with SK Hynix from the outset.
On June 7th, NVIDIA and SK Hynix officially announced the establishment of a multi-year technology partnership to jointly develop next-generation memory that matches NVIDIA’s AI infrastructure roadmap. It is understood that the cooperation covers a range of NVIDIA’s personal and cloud-side product lines, including the NVIDIA Vera Rubin AI supercomputer, Vera CPU, PCs equipped with RTX Spark, and the Jetson Thor robot computing platform. The announcement stated that the cooperation aims to ensure the supply of advanced memory, to cope with the long development cycles, complex manufacturing processes, and high capital investment of such products, thereby supporting the continuous construction of global AI factories. The announcement also listed several new markets that SK Hynix will expand into, pioneered by NVIDIA, including AI infrastructure, personal AI, and physical AI.
02 AI Repays Chip Manufacturing
In addition to supplying memory, SK Hynix has begun to apply NVIDIA’s AI technology to its own chip design and manufacturing processes. Similar cooperation has previously been implemented at TSMC, the most typical example being “computational lithography.” According to the announcement, SK Hynix is using NVIDIA’s CUDA-X libraries and AI to accelerate semiconductor simulations, covering areas such as Technology Computer-Aided Design (TCAD) and computational lithography. The two sides are also promoting the expansion of these tools into the semiconductor Electronic Design Automation (EDA) and simulation ecosystem, paving the way for tripartite cooperation between chip manufacturers, NVIDIA, and EDA software vendors.
This means that the cooperation between the two parties is no longer limited to SK Hynix’s internal use, but is exploring a model that can be rolled out to the entire semiconductor industry. In the manufacturing segment, SK Hynix is advancing the development of wafer fab digital twin functionality, with the goal of achieving fully autonomous factory operations. The foundation for this work is NVIDIA’s Omniverse platform. With the Omniverse libraries and OpenUSD workflow, SK Hynix can build 3D factory scenes for visualizing, simulating, and optimizing complex semiconductor manufacturing environments. At the factory operations level, these digital twin functions can also be connected to NVIDIA’s cuOpt decision optimization engine and Metropolis platform for scheduling autonomous mobile robots and other assets within the wafer fab. The announcement also revealed that the two companies are exploring the integration of digital twins with existing traditional software and intelligent agent AI workflows, enabling AI systems to perform inference, automate tasks, and improve manufacturing decisions based on wafer fab data.
03 Laying the Groundwork Six Months in Advance
As early as October 2025, NVIDIA and SK Hynix had announced a large-scale infrastructure cooperation. At that time, SK Group was building an AI factory equipped with over 50,000 NVIDIA GPUs, with the first phase planned for completion by the end of 2027. Once completed, it is expected to be one of the largest AI factories in South Korea. The factory adopts a “GPU-as-a-service” model, open to SK Group’s subsidiaries and external organizations, aiming to accelerate the digital transformation and industrial innovation of South Korean industries.
SK Telecom is also undertaking specific deployment work. As an NVIDIA cloud partner, SK Telecom plans to build an industrial AI cloud in Asia using NVIDIA RTX PRO 6000 Blackwell server-grade GPUs, with an initial deployment of over 2,000 GPUs, specifically for running Omniverse workloads and providing computing power support for SK Hynix’s semiconductor manufacturing, wafer fab digital twins, and internal AI agents. Jensen Huang also revealed during his visit to South Korea that he is in discussions with telecommunications companies because future AI will utilize telecommunications networks. This aligns with the direction of SK Telecom’s participation in the cooperation.
04 Three Suppliers Share HBM4 Orders
Although NVIDIA and SK Hynix have signed a multi-year technology cooperation agreement, NVIDIA has not put all its eggs in one basket when it comes to HBM4 supply. Jensen Huang explicitly stated to reporters upon arriving in Seoul: “All three suppliers have been qualified. All three suppliers have entered production, and they are all competing to support Vera Rubin.” These three suppliers correspond to Samsung Electronics, SK Hynix, and Micron Technology.
In his keynote speech at Computex Taipei, Jensen Huang confirmed that Vera Rubin is in full production and scheduled for delivery in the third quarter of this year. This system is built around NVIDIA’s Vera CPU and Rubin graphics core clusters, with each server rack system equipped with terabytes of HBM4 memory. In terms of actual HBM4 progress, SK Hynix remains in the lead. Reuters reported last September that SK Hynix had completed internal certification of its HBM4 chips and established a production system for customers, aiming to complete mass production preparations for 12-layer HBM4 products in the second half of 2025. Kim Sunwoo, a senior analyst at Meritz Securities, predicted at the time that SK Hynix would maintain a market share of just over 60% in 2026 for HBM, thanks to early supply to key customers and the resulting first-mover advantage.
05 Chip Shortage to Last for Several Years
The situation of having three suppliers for HBM4 does not mean the supply pressure will be relieved. After the dinner on Sunday, Jensen Huang also gave a less optimistic assessment. He told the media present that the shortage of memory chips will not end soon. “The entire industry supply chain—from wafers to packaging to silicon photonics… everything is in short supply because the demand is so high. This situation will continue for several years.”
The background to this statement is the almost insatiable consumption of advanced memory by global AI factory construction. The shortage Jensen Huang is referring to is not a lack of one specific item, but rather a tight supply in almost every segment of the industry chain. NVIDIA’s launch of Vera Rubin, promotion of AI factories, and entry into the personal AI and physical AI fields—each of these actions increases the demand for memory. This is why he said all three HBM4 suppliers are competing to support Vera Rubin. No one wants to be left behind in a situation of insufficient supply. While SK Group was a focus of this trip to South Korea, it was not Jensen Huang’s entire schedule. Upon arrival, he revealed that he had arranged meetings with Hyundai Motor, LG, SK, Samsung, and Naver. He also revealed that NVIDIA is actively recruiting personnel for its new research and development center in South Korea. From these movements, it is evident that NVIDIA is systematically deepening its ties with the entire South Korean technology industry, with SK Group being a key link, but not the only one.
[Author: Su Yang Editor: Xu Qingyang]
NVIDIA-South Korea Alliance: Catalyst for AI Crypto Narrative and Infrastructure Tokens
Jensen Huang’s timely intervention in South Korea’s “Black Friday” market collapse wasn’t merely a PR stunt—it was a masterclass in orchestrating market sentiment while simultaneously reinforcing NVIDIA’s strategic positioning in the AI ecosystem. For crypto investors, this event signals more than just traditional market stabilization; it highlights the growing interdependence between AI hardware, semiconductor technology, and blockchain infrastructure investments.
The Hype Cycle Meets Reality: AI Crypto Tokens Poised for Rebound
Huang’s confirmation that memory chip shortages will persist for “several years” validates the long-term AI bull thesis that has been underpinning AI-related cryptocurrencies. The Vera CPU’s requirement for advanced HBM4 memory creates a structural demand that favors established players like SK Hynix, Samsung, and Micron—all of which are now confirmed NVIDIA suppliers.
For crypto investors, this translates directly to opportunities in AI infrastructure tokens. Projects like Fetch.ai (FET), SingularityNET (AGI), and Ocean Protocol (OCEAN) stand to benefit as the AI industry’s insatiable demand for computing resources continues to grow. Huang’s explicit statement that “if you are a shareholder of an AI company, you will be happy” should be interpreted as a broad endorsement of the entire AI ecosystem, including blockchain-based alternatives to centralized AI infrastructure.
Beyond Hype: NVIDIA’s Strategic Positioning and Crypto’s Competitive Edge
What’s particularly noteworthy is NVIDIA’s expansion into semiconductor manufacturing through digital twins and AI-enhanced production processes. This positions NVIDIA as not just a hardware provider but as an industrial AI enabler—a move that directly competes with blockchain projects aiming to tokenize or decentralize manufacturing processes.
For crypto investors, this creates both headwinds and tailwinds. On one hand, NVIDIA’s centralized approach to industrial AI could marginalize blockchain alternatives. On the other hand, it validates the underlying premise that AI will transform traditional industries, creating opportunities for blockchain solutions that offer transparency, efficiency, and decentralization.
The Omniverse platform integration with SK Hynix’s wafer fabs represents a significant development. For crypto investors, this signals that the boundary between physical and digital infrastructure is blurring—a trend that benefits projects focused on digital twins, metaverse infrastructure, and tokenized physical assets.
The Memory Crunch: Supply Chain Constraints and Blockchain Solutions
Huang’s candid admission about persistent chip shortages highlights vulnerabilities in centralized semiconductor supply chains. This creates a compelling use case for blockchain-based supply chain solutions in the semiconductor industry.
Projects like IOTA with its Tangle technology for supply chain tracking, or VeChain (VET) with its enterprise-grade supply chain solutions, could see increased relevance as companies seek more resilient, transparent alternatives to traditional supply chain management. The memory shortage isn’t just a hardware constraint—it’s an opportunity for blockchain to demonstrate its value in solving real-world infrastructure problems.
The AI Factory Race: Decentralized Computing’s Moment?
SK Group’s plans to build an AI factory with over 50,000 NVIDIA GPUs represents a massive concentration of computing power. While this centralized approach dominates the current landscape, it simultaneously creates a market opportunity for decentralized computing platforms.
Projects like Render (RNDR), iExec (RLC), and Akash (AKT) that facilitate decentralized GPU sharing could benefit from the high costs and limited access to centralized AI infrastructure. As Huang himself noted, “future AI will utilize telecommunications networks”—a statement that hints at the distributed nature of future AI systems, potentially favoring decentralized solutions.
Risks and Overhyped Opportunities
Not all AI-related crypto tokens will benefit equally. Investors should be wary of pure hype plays lacking tangible products or partnerships. The NVIDIA-South Korea alliance demonstrates that real-world adoption requires more than just marketing—it requires technical integration and enterprise partnerships.
Additionally, the dominance of established players like NVIDIA, Samsung, and SK Hynix could stifle innovation in the blockchain AI space. Crypto projects that attempt to compete directly with these giants on their own terms are likely to face significant headwinds.
Conclusion: Strategic Entry Points for Crypto Investors
For experienced crypto investors, the NVIDIA-South Korea alliance presents several strategic entry points:
- AI infrastructure tokens with real partnerships and product development
- Blockchain supply chain solutions targeting the semiconductor industry
- Decentralized computing platforms that offer alternatives to centralized AI infrastructure
- Tokenized physical asset projects focused on industrial and manufacturing applications
Huang’s market-saving visit was more than just a temporary boost for South Korean stocks—it was a clear signal that the AI revolution is here to stay, creating both challenges and opportunities for the blockchain ecosystem. The smart money will recognize that the future of AI isn’t just about centralized computing power—it’s about the infrastructure that enables, secures, and democratizes that power.