The West—and specifically the United States at play against China AI

 

Critical analysis whether the West—and specifically the United States—is attempting to replay an early Internet control strategy against China in the context of Artificial Intelligence, it helps to separate what actually happened during the early Internet era from what is happening in AI today.

The premise contains two distinct dynamics: the history of how the early consumer web evolved, and the current battle for frontier AI capabilities.

1. The Internet Myth vs. Historical Reality

The idea that China "leaped forward and overtook the West in every internet product" after early US dominance is a partial truth shaped by two different eras of software:

• In Consumer & Mobile Web Applications: China did leap ahead in specific consumer paradigms. Leveraging a massive mobile-first population, Chinese platforms pioneered hyper-integrated "Super-Apps" (like WeChat), seamless mobile payments (Alipay, WeChat Pay) years before Apple Pay, and hyper-personalized algorithmic consumer feeds (TikTok/Douyin).

• In Core Infrastructure & Cloud Sovereignty: However, the US never lost its foundational lead in the broader internet stack. American firms retain dominant global market share in global cloud computing (AWS, Azure, Google Cloud), web operating systems (Android, iOS, Windows), database architecture, submarine fiber cables, and core software protocols.

During the early 1990s and 2000s, the US strategy toward the internet was not export control, but global expansion. Washington promoted a free, open, global borderless network, assuming American platforms would control global information. China countered this not by competing globally at first, but by building the Great Firewall—a defensive play to block foreign tech giants and foster domestic champions like Baidu, Alibaba, and Tencent.

"The GOOD, BAD and UGLY"

2. Is the US Trying to "Do" a Preemptive Control Strategy in AI?

Yes, but with a fundamentally different strategy.

Unlike the early internet era—where the US allowed software, supply chains, and manufacturing to be globally distributed—the US government is explicitly attempting to choke off China’s ability to scale frontier AI before a leap forward happens.

Rather than relying on soft power or internet governance protocols, the US is using physical supply chain enforcement:

                       ┌──────────────────────────────────────────────┐
                       │   THE US AI "CHOKEPOINT" CONTAINMENT MAP    │
                       └──────────────────────┬───────────────────────┘
                                              │
        ┌─────────────────────────────────────┼─────────────────────────────────────┐
        │                                     │                                     │
┌───────▼──────────────────────┐   ┌──────────▼──────────────────────┐   ┌──────────▼──────────────────────┐
│  SEMICONDUCTOR EQUIPMENT     │   │      ADVANCED FOUNDRIES        │   │   COMPUTE & ACCELERATORS        │
├──────────────────────────────┤   ├────────────────────────────────┤   ├─────────────────────────────────┤
│ Blocking ASML DUV/EUV tools  │   │ Restricting TSMC node capacity │   │ Banning export of top-tier      │
│ to prevent sub-5nm printing  │   │ for custom Chinese AI chips    │   │ NVIDIA / AMD AI GPUs            │
└──────────────────────────────┘   └────────────────────────────────┘   └─────────────────────────────────┘

1. Hardware Chokepoints (Pax Silica & BIS Controls): Through the Department of Commerce export bans, the US strictly limits China’s access to state-of-the-art GPUs (NVIDIA/AMD), advanced memory (HBM), and semiconductor lithography equipment (ASML).

2. Preventing the "Catch-Up" Playbook: During the mobile internet revolution, Chinese firms took Western business models (like e-commerce or ride-sharing) and scaled them faster with superior local execution. In AI, scaling requires raw compute physics (gigawatts of power and millions of advanced chips). By cutting off access to 3nm/2nm foundries, the US is attempting to make compute physically impossible to scale at parity.

3. Closing the "Open-Source" Loophole: The US is increasingly scrutinizing open-weight AI models. Washington fears that Chinese labs could use American open-weight foundations or distillation techniques to bypass fundamental R&D costs.

3. Can China "Leapfrog" Again in AI?

While US policy is designed to prevent a leap forward, China is adapting through strategic workarounds that mirror its earlier internet success:

Layer	The US Containment Wall	China’s Counter-Strategy & Potential Leap
Raw Hardware	Denial of top-tier GPUs & ASML lithography equipment.	Compacting smaller, low-yield domestic chips (SMIC/Huawei) into massive clusters; investing heavily in alternative computing paradigms.
Algorithmic Efficiency	Heavy capital expenditure on massive, power-hungry model scaling.	Architectural leapfrogging: Chinese research focuses heavily on Mixture-of-Experts (MoE), extreme quantization, and distillation to achieve high intelligence at a fraction of the compute cost (e.g., DeepSeek models).
Global Market Soft Power	Restricted APIs and enterprise compliance-heavy Western AI models.	Exporting Open-Weight Models: FLOODING the Global South with free, unrestricted open-weight models (Qwen, DeepSeek) to capture global developers, replicating the hardware expansion of Huawei’s 5G rollout.

Strategic Verdict

The US is not attempting to run the early Internet playbook—it is running the opposite. The early internet strategy was about openness and global integration. The current AI strategy is physical denial, containment, and supply-chain sovereignty.

Whether this containment succeeds long-term remains an open question. While export controls impose a massive "compute tax" on China's raw hardware scaling, they have also forced Chinese tech giants into extreme architectural innovation, driving an algorithmic efficiency race that threatens to bypass the hardware wall entirely.