In-depth Analysis of the AI Storage Expansion Logic: Understanding the Industry's Underlying Dynamics from NVIDIA's Perspective!

🔍 The Storage Underlying Logic from NVIDIA's Perspective

If we are not standing from the perspective of ordinary retail investors, but rather from the perspective of CEO Jensen Huang, to truly operate a company, the real concern is not the additional procurement premium, but rather that your upstream, storage price increases too much, ultimately blocking the shipment rhythm of your own GPUs, dragging down the advancement of the entire AI industry chain.

Currently, AI servers cannot run solely on GPUs; they require a complete infrastructure system: including GPUs, HBM (High Bandwidth Memory), enterprise-grade high-performance storage, network cards, resistors and capacitors, power supply, cooling, data centers, system integration, and other full-chain supporting components.

In fact, after years of development, what the AI industry lacks is the overall system capability. In the era of traditional servers, storage demand was relatively controllable, and supply and demand were basically matched, so production capacity reached a certain equilibrium level. However, with the global wave of AI data center expansion and the development of sovereign AI, after large-scale terminal demand materializes, all aspects such as large model training, inference, system scheduling, parameter reading, caching, and communication are consuming storage capacity.

📈 The Core Drivers of This Round of Storage Price Increases

The core reason for the rise of storage targets like Micron and SanDisk in this round is not driven by retail investors. Whether looking at single stock prices or option hedging costs, ordinary investors hold an extremely low proportion. The market trend is dominated by industrial logic.

An exchange rule: when the number of holders is insufficient, meaning liquidity is not sufficient, either the company repurchases shares or raises the offer price (to meet the per capita shareholding value requirement). Prices rise, and companies raise more funds to complete expansion financing.

Industry's intrinsic nature: The storage industry is a typical cost-performance race track. There will be no absolute efficiency gap between leading manufacturers like Samsung, SK Hynix, Micron, and SanDisk because storage chips do not follow Moore's Law. Current technology specifications have reached 10 nanometers; making them smaller will cause mutual interference and performance issues. Therefore, industry competition ultimately boils down to a contest of production capacity, yield rate, cost, customer validation, and supply-demand cycles.

🧮 The Industrial Layout Calculation from NVIDIA's Perspective

Integrating upstream supply (through methods like equity investment, financing, signing long-term agreements) will not solely support a single storage manufacturer. Instead, it will support all companies with AI high-performance storage production capacity to expand. The core objective is to prevent storage manufacturers from monopolizing and raising prices. By promoting supply increases across the entire industry, storage prices can return to a reasonable range.

Even investing billions in strategic support funds as a test, resulting in a small book loss is completely worthwhile. Because once storage supply is sufficient, AI server costs will decrease, NVIDIA GPU shipment rhythms will become smoother, leveraging subsequent industry expansion worth trillions.

💡 The Deep-Running Logic of the Market Trend

Focus on the overall financing progress and expansion actions of manufacturers to determine whether they have completed capacity construction through the capital market.

This year, the semiconductor sector has shown a significant rotation effect. Taking storage as an example, the surface drivers of this round's rise are shortages, the explosion in HBM demand, and AI demand pull. The underlying logic is that AI infrastructure needs the storage sector to complete financing through rising market prices, supporting companies to build new capacity and avoid future AI server supply being blocked by storage resources.

This is deep cooperation between the capital market and industrial expansion: market prices rise → companies obtain financing → capacity construction is completed → supply is released to support AI industry advancement.

⚠️ Key Judgment Points for the Market Trend

When storage capacity expansion reaches the peak of the normal distribution and signs of capacity overflow appear (indicating a shift towards destocking), the logic for storage price increases may face a turning point in the market.

Therefore, the core judgment criterion for the storage market trend is not product price increases, but rather confirming the progress stage of this round of financing and expansion:

• Whether funds have been raised
• Whether production lines have been constructed and completed
• When supply will be released
• When prices will fall back
• And whether downstream players like NVIDIA still need to continue supporting upstream segments like storage.

AI Industry Ecosystem Competition Upgrades The competition in the AI industry has already upgraded from single-model competition and chip competition to full-ecosystem competition: NVIDIA occupies a dominant position in the computing power ecosystem. Major model companies like Zhipu, MinMax, Claude, and OpenAI, by providing computing power tools to global researchers and developers, have bound the top-tier AI research ecosystem, forming content ecosystem barriers. All computing infrastructure manufacturers like Microsoft, AMD, and Amazon cannot detach from this ecosystem.

Looking back at the market trend, the entire AI industry chain is undergoing a round of infrastructure revaluation:

GPUs were the first wave leading the trend, cloud vendors were the second wave (along with ASIC custom chips), storage is the third wave.

Subsequent tracks like scheduling, power supply, networking, cooling, packaging equipment, and materials may also usher in new market opportunities, discussing the next category's "super cycle."

Against the backdrop of multiple storage manufacturers expanding production, the voice of semiconductor equipment in the market has been amplified. Moreover, as one of the most upstream links in the chip manufacturing industry chain, often called the "mother machine" of chip production, it could become a side-line speculative theme under the expansion background.

In the investment for a new wafer production line, equipment expenditure usually accounts for 70-80%. From silicon wafer cleaning, lithography, etching, thin film deposition, to ion implantation, measurement, and inspection, each process step has a dedicated type of equipment behind it. The process level of the equipment directly determines how many nanometers a wafer fab can achieve.

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