From hardware to cloud: Exploring the growth trend of AI cycles

This year's wave is truly a surge in the AI cycle. Currently, from the most fundamental hardware to various production-side services, we see a series of stock growth linkages.

1. AI Hardware Growth

First is AI hardware. NVIDIA, which was considered overpriced at around 100 at the beginning of the year, has now reached around 160 after facing challenges like tariff exports.

2. Cloud Services Growth

However, many companies won't directly purchase AI hardware due to high costs and maintenance hassles. Thus, the flexibility and convenience of cloud computing have become an excellent carrier for AI computing power and products.

First is Google Cloud. Benefiting from the continuous refinement of TPU technology, which provides cheaper computing power, it secured deals with Meta, Deutsche Bank, and JP Morgan, changing the market's perception of Google Cloud.

Next is Alibaba Cloud, which had been stagnant for years with declining growth. This year's financial report shows AI as a new growth engine, and its stock price soared from around 120 to 140.

Then there's Oracle, which has recently seen a revival. By upgrading from data warehouses to AI computing warehouses, its cloud infrastructure is growing rapidly.

Other cloud services like Kingsoft Cloud are also rising.

3. The AI Cycle

I remember AI first entered the public consciousness with AlphaGo's match in 2016. Alibaba Cloud had already released AI products like facial and image recognition as early as 2015.

Though those early products pale in comparison to today's, the seeds were sown. A decade of brewing has led to this global wave, making AI a truly worldwide business, far surpassing the scale of contemporaneous trends like the metaverse and Web3. Those who understand cycles and production chains likely reaped significant rewards this year.

4. Future Trends

With limited insight, I foresee:

1. Centralized AI infrastructure and related production-side segments will continue to grow, though possibly at a slower pace. The transition from traditional IT infrastructure to AI infrastructure still has a vast market share to capture.

2. As edge technology and models mature, edge-based AI will gradually rise, akin to how early computing shifted from large centralized systems to today's powerful, compact devices like smartphones and PCs.

3. User-facing touchpoints and entry points will remain highly valuable.

In this context, Google is an all-rounder, excelling in all three areas. Xiaomi should aim to seize the latter two opportunities.

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