Industry Insights: AI's Role in Filling the Market Gap

Micron's FYQ2 financial report, released on March 20, showed exceptional performance, exceeding expectations and achieving profitability earlier than anticipated. HBM3E has achieved mass production, but because its wafer consumption is three times that of DDR5, its future production capacity growth is very limited and will be in short supply for a long time. Our previous analysis in October delved into the specific dynamics of HBM demand growth.

In recent developments, Sam Altman, CEO of ChatGPT OpenAI, expressed interest in collaborating with industry giants Samsung Electronics and SK Hynix to venture into AI chip development. While OpenAI doesn't intend to open-source large model code, our goal is to provide free and easy access to AI assistants, ensuring broader user accessibility.

Additionally, the exciting NVIDIA GTC on March 18th not only released the powerful Blackwell chip GB200, but this also strengthens the fact that NVIDIA's business route never stops at one chip company. Through its launch of NIM, their AI deployment platform, NVIDIA's clear goal is to convey the concept of an ecosystem of AI environments and to speed up the business paths of companies that are accelerating AI lines. This underscores NVIDIA's role in driving a resurgence in the semiconductor market through its holistic AI ecosystem strategy. However, despite the market's AI-driven momentum, downstream demand growth remains sluggish, presenting challenges for AI integration into daily operations, particularly for SMEs with conventional business models.

Taking these consultations together, we need to make several things clear: the wave of AI technology led by Nvidia is driving a rebound in the semiconductor market. However, all leading companies are also clearly aware of the weak growth in downstream market demand. The application scenarios of AI are already clear, and the technical implementation is just around the corner, but the complexity of integrating AI technology into daily operations is difficult for many small and medium-sized enterprises to cope with. Besides start-up technology companies with AI as the core of their development, most companies with traditional business models are unable to invest a large amount of money at one time for business upgrades. Even though the benefits of integrating AI into daily operations have become clear, the talents on the market who truly master AI technology have been taken away by major manufacturers. The operating and sunk costs of building an AI operation platform may be a huge investment in the current uncertain environment. Looking back at the previous news, it is clear that everyone has seen the huge gap between excellent technology and technology implementation. Although most people regard NVIDIA intelligent deployment as a commercial attack on cloud services, we would rather understand them as effective communication of downstream needs. Whether or not the downstream market pays the bills is based on a clear intelligent experience.

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