NVIDIA was one of the few semiconductor vendors with significant announcements, and a larger presence over last year’s COMPUTEX. The company has forged closer ties with Taiwan, in no small part linked to Jensen Huang’s personal ties to the island, and this was also symbolically demonstrated by the decision to build another “Headquarters (HQ)” near Taipei named NVIDIA Constellation. This is also a manifestation of the divergence from the United States and the rest of the world brought on by the risk of trade restrictions, and a sign of Taiwan’s importance in the high-end technology supply chain.
NVIDIA’s mission is to define tomorrow’s Artificial Intelligence (AI) and capture as much value from AI Personal Computers (PCs) and AI data centers, leveraging its extensive channel and ecosystem partners’ strengths. This strategy makes gains every year in outmaneuvering competitors and creating an indispensable ecosystem. It is a multi-pronged assault focused on democratizing access, building an unassailable full-stack advantage, and controlling the critical nervous system of AI: the interconnect.
NVIDIA’s ultimate vision is the “AI factory” where computers directly translate to revenue. This narrative reframes its high-performance systems not as costs, but as essential manufacturing equipment. The plan to build out hundreds of thousands of GB200s this year alone (for giants like OpenAI and Microsoft) underscores the massive scale of this buildout.
Its competitive strategy against rivals (implicitly AMD, Intel, and custom Application Specific Integrated Circuit (ASIC) makers) involves relentless annual performance improvements. Advising customers to “only buy some of what they need every year” is a confident Go-to-Market (GTM) message that promises continuous advancement. This, combined with the surging compute demand from reasoning models and Agentic AI of 100X to 1,000X, ensures a sustained upgrade cycle and steady revenue streams for those locked into the ecosystem.
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GTM Pillar 1: Expanding Market Penetration—from Enterprise to Every Developer
The announcement of the air-cooled RTX PRO enterprise AI server with Ethernet networking is a direct play to penetrate traditional enterprise Information Technology (IT). By supporting standard x86 workloads (Red Hat, etc.), NVIDIA lowers the adoption barrier, making it easier for businesses to integrate AI without overhauling existing infrastructure—a tactic to win over IT departments wary of specialized, complex hardware. This appeals to enterprise IT departments wary of the vendor lock-in of InfiniBand, and those lacking the budget or infrastructure to build liquid-cooled setups designed to handle more performant Graphics Processing Units (GPUs). This is amplified by the inclusion of NVIDIA (alongside Intel, AMD, and Qualcomm) in Microsoft’s newly announce Windows Machine Learning (ML), an evolution of Windows Copilot Runtime, designed as a unified platform to streamline the entire AI developer lifecycle on Windows Application Programming Interface (API). This channel strategy embeds NVIDIA deeper into the vast Windows ecosystem, reaching millions of desktops and workstations. Aside from traditional enterprise AI, RTX PRO servers will also target Omniverse and industrial applications, such as robotics and digital twins.
For 30 million software developers, the DGX Spark system is a targeted GTM offering. By addressing the costly “idle time” in cloud development and promising a rapid (~6-month) Return on Investment (ROI), NVIDIA appeals directly to developer productivity and budget concerns. Making it available through all OEMs is a classic channel expansion strategy, maximizing reach and making NVIDIA hardware readily available on a global scale. The US$3,999 price tag for the 4 Terabyte (TB) version may be a hindrance for real AI democratization among a broader base of developers, with Intel and AMD launching discrete GPUs targeting entry-level workstations.
GTM Pillar 2: The Full-Stack Moat & Ecosystem Lock-in
NVIDIA's core competitive advantage lies in its algorithm-first, full-stack design. Unlike Central Processing Unit (CPU) vendors relying on compilers, NVIDIA’s accelerated computing paradigm, built around CUDA, creates a stickier ecosystem. This software layer made up of libraries to accelerate diverse workloads is constantly improving in efficiency, and is a formidable competitive moat that NVIDIA’s rivals find incredibly difficult to replicate.
Omniverse, a 7-year development effort, is a prime example of this platform strategy. Re-architected for scalability, it is positioned with the RTX PRO as the “Omniverse” (digital twin/robotics) computer. Rather than selling hardware, it is selling entry into a unique, high-value ecosystem, creating lock-in for industries adopting these advanced simulation and collaboration tools.
NVLink Fusion: The Battle for Interconnect
The battle for AI supremacy is increasingly being fought at the networking and interconnect levels. NVLink Fusion is an expansion of NVIDIA’s addressable market by recognizing the importance of compute Intellectual Property (IP) from other vendors. Customers wishing to leverage the scale-up technology introduced by NVL72 will be able to use Cadence and Synopsys’ Electronic Design Automation (EDA) tools to deploy, e.g., Qualcomm CPUs to work alongside Blackwell GPUs in a system connected by NVLink. Diverse hardware ecosystems will thus “fuse” and leverage NVIDIA's interconnect technology. This strategic move is reportedly based on feedback from customers actively seeking NVLink because “UALink isn't going so well.” NVIDIA is capitalizing on this by expanding NVLink's market opportunity beyond NVIDIA's own systems, allowing hyperscalers and others to integrate their IP via custom design houses like Marvell into NVL72 (and future generations). The goal is to create a de facto standard, making it harder for competing interconnects to gain traction.
Conclusion: AI Dominance Remains
NVIDIA's current strategy is a master class in building and defending a dominant market position. By broadening its reach into enterprise IT with RTX PRO, creating an unparalleled full-stack ecosystem (CUDA, Omniverse), and strategically controlling critical interconnect technology (NVLink Fusion), NVIDIA is aggressively engineering the future of AI infrastructure. While geopolitical headwinds and resurgent competitors like Huawei present challenges, NVIDIA's relentless innovation, strategic GTM, and vast ecosystem position it at an advantage for the foreseeable future.
More AI technology developments from COMPUTEX 2025 can be read in the articles below:
- The Emergence of a New Battleground: Intel Versus AMD in AI Workstations
- Qualcomm's AI Strategy: Leveraging Connectivity Legacy Across Edge AI, Capturing AI PC Market Share, and a Foray into Data Center via NVLink Fusion