Jensen Huang’s Visit to Korea (Part 3): The NVIDIA CUDA Barrier and the Big Tech Counterattack

Let's learn more about Nvidia CEO Jensen Huang's visit to South Korea

— Countermeasures from Musk, China, and Europe, alongside Opportunities and Crises for India and South Korea — In June 2026, the afterimages left by NVIDIA CEO Jensen Huang’s visit to South Korea were nothing short of spectacular. His consecutive meetings with the heads of Korea’s top conglomerates—including Samsung Electronics, SK Hynix, Naver, and Hyundai Motor—seemed to prove just how consolidated the "AI infrastructure alliance" built by NVIDIA truly is. Behind the glitz and glamour, however, global Big Tech firms and major nations are hard at work seeking massive alternatives to avoid being trapped under NVIDIA’s suffocating dominance. Because this technological monopoly's fortress is so robust, it is difficult to definitively predict the downfall of the NVIDIA empire in the short term. Nevertheless, competitors outside the fortress walls are solving their long-term survival equations by weaponizing their own "captive consumer markets." Let's look into the flip side of the alliance shown during Jensen Huang’s visit: the true nature of the monopoly and the practical countermeasures being taken by an increasingly diversified global tech ecosystem. 1. The Reality of NVIDIA’s Monopoly: A "Semi-Open Software Lock-In," Not Hardware Many believe NVIDIA dominates the market simply because its Graphics Processing Units (GPUs) offer overwhelming performance. However, the truly terrifying barrier to entry lies not in the hardware, but in the software ecosystem. An 80–90% Share of the AI Data Center GPU Market: From Blackwell , which is essential for LLM (Large Language Model) training and inference, to the next-generation Vera Rubin platform, NVIDIA’s AI accelerators (dedicated AI computing semiconductor packages) command absolute dominance over the market. The Software Shackle, "CUDA": This is the core pillar of NVIDIA’s monopoly. Distributed for free in 2006, the CUDA development platform has become the "default standard" used by AI developers and researchers worldwide to write code over the past 20 years. ♣ The Origin of the Name "CUDA" CUDA stands for Compute Unified Device Architecture . True to its name, it embodies Jensen Huang’s obsession: to allow software developers to universally integrate and control the powerful computing capabilities of GPUs using standard programming languages (C/C++) , without needing complex graphic commands. The Trap of a Seemingly Low-Barrier "Semi-Open Structure": CUDA is not a completely closed system. It features a "semi-open structure" that integrates seamlessly with global open-source AI frameworks like PyTorch and TensorFlow. By providing convenience to developers, NVIDIA has deeply rooted them into its ecosystem. Consequently, this functions as a highly sophisticated platform lock-in strategy , making it impossible for the code to run without NVIDIA hardware. The Real Core is TCO (Total Cost of Ownership): The reason enterprises cannot easily switch to alternative chips from AMD or Intel is not merely the price of the chips. Migrating to another company's hardware requires rewriting existing CUDA-based code, incurring years of development time and astronomical engineering costs. When factoring in electricity bills, operational stability, and talent recruitment costs, looking at it through the lens of TCO invariably leads companies to the conclusion that sticking with NVIDIA is the most efficient choice. 2. The Counterattack of Giants with "Captive Markets": Vertical Integration and Hybrid Strategies The reason the anti-NVIDIA movement is so formidable in the long run is that the entities seeking alternatives possess not only chip design capabilities, but also massive downstream industries and domestic markets capable of immediately absorbing 100% of the chips produced for their own services or nations. While a short-term victory may be elusive, this is the backdrop that enables a long-term war of attrition. ① Elon Musk: A Hybrid Strategy of "Dojo" and Infrastructure Alignment Elon Musk is pursuing vertical integration by leveraging a guaranteed captive market where proprietary chips can be deployed immediately: Tesla (autonomous driving), xAI (the AI 'Grok'), and SpaceX (space and satellites). ♣ The Origin of the Name "Dojo" Dojo (道場) means a place to practice martial arts in Japanese. Musk personally named the project to signify a venue where artificial intelligence for Full Self-Driving (FSD) software is "honed and trained through grueling practice into a martial arts master," utilizing the immense volume of driving video data collected from Tesla vehicles worldwide. A Realistic Alternative, the Hybrid Route: Tesla has developed and deployed its proprietary AI supercomputer chip, the "D1" (Dojo chip), optimized for video analysis . However, given NVIDIA’s ongoing hardware hegemony, Musk is adjusting the pace of the Dojo project to balance proprietary chip development with the sheer scale of NVIDIA's infrastructure. By utilizing massive NVIDIA GPU clusters simultaneousl