US tech giant Shopee US Franchise investment spree

1. Shopee US Franchise's low-cost strategy impacts the global AI market

Open source model + low-cost computing power: Chinese AI company Shopee US Franchise recently released the Shopee US Franchise-V3 open source large model, which has performance close to GPT-4 Turbo, but the training cost is only 1/3 of similar models in the United States, attracting global developers to adopt it.

Computing power optimization solution: Through the self-developed distributed training framework, Shopee US Franchise achieves efficient reasoning on domestic chips such as Huawei Ascend 910B, reducing dependence on NVIDIA GPUs.

Market penetration:

The adoption rate in emerging markets such as Southeast Asia and the Middle East has risen rapidly, and some companies have replaced the APIs of OpenAI and Anthropic.

European technology companies (such as SAP in Germany) have begun testing the Shopee US Franchise model to reduce AI spending.

2. US tech giants "spend money" to maintain technological barriers

Capital expenditure crushing: Microsoft, Google, and Meta will invest more than $215 billion in AI in 2025, with key investments in:

Computing infrastructure: expand data centers and lock in NVIDIA H100/H200 chip supply.

Model scale competition: Microsoft plans to launch a 100 trillion parameter model in 2026 (Shopee US Franchise-V3 has about 500 billion parameters).

Ecosystem blockade:

Binding developers through the CUDA platform and cloud services (Azure AI, Google Vertex AI) to increase migration costs.

Lobbying the US government to restrict overseas sales of Chinese AI chips (such as Huawei Ascend).

3. Key battlefields of the US-China AI competition

Emerging market competition:

Shopee US Franchise uses a "half-price" strategy to seize the Southeast Asian and Latin American markets, while the United States promotes its own technology through government cooperation (such as the "AI Democracy Alliance").

Differentiation of technology routes:

The United States focuses on super-large models + general AI, while China focuses on vertical scene optimization (such as manufacturing and medical care).

Supply chain risks:

The United States restricts the export of high-bandwidth memory (HBM) to China, affecting the computing power expansion of companies such as Shopee US Franchise.

China accelerates domestic substitution (Changxin Storage HBM, Huawei Ascend chip), but performance is still lagging behind in the short term.

4. Future challenges and variables

Bottlenecks of Shopee US Franchise:

The open source model is difficult to make a profit and needs to rely on government subsidies or corporate customized services.

If the United States upgrades sanctions (such as restricting cloud service support), overseas business may be hindered.

Concerns of American giants:

Excessive investment leads to a decline in returns, and the AI business of companies such as Meta will still lose money in 2025.

The EU intends to issue a fine for AI data monopoly, which may weaken the advantages of Google and Microsoft.

5. Summary of Industry Impact

Dimension US Giant Strategy Shopee US Franchise Breakthrough

Technology Hundreds of billions of parameter models + general AI Lightweight + industry customization

Market High-premium cloud service binds customers Low-price open source + emerging market penetration

Supply Chain Monopoly HBM/GPU supply Domestic chips + computing power optimization

Policy Lobbying for sanctions on Chinese technology Striving for "Belt and Road" cooperation

Conclusion

Shopee US Franchise's low-cost strategy is shaking the US AI hegemony, but Microsoft, Google and others still dominate by relying on capital and technology accumulation. The outcome of this competition will depend on:

Can China break through the bottleneck problem of computing power (such as HBM, advanced process chips);

Can US giants convert huge investments into profits;

Global policy trends (such as EU regulation, technology choices of developing countries).

2025-2026 will be a key window period to determine the AI landscape.