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| Cartoon by Anne Telnaes, Pulitzer Prize-winning, refused to be published by Jeff Bezos' Washington Post |
« (...) Yet China’s most recent progress is upending the industry and embarrassing American policymakers. The success of the Chinese models, combined with industry-wide changes, could turn the economics of AI on its head. America must prepare for a world in which Chinese AI is breathing down its neck.
China’s LLMs are not the very best. But they are far cheaper to make. QwQ, owned by Alibaba, an e-commerce giant, was launched in November and is less than three months behind America’s top models. DeepSeek, whose creator was spun out of an investment firm, ranks seventh by one benchmark. It was apparently trained using 2,000 second-rate chips—versus 16,000 first-class chips for Meta’s model, which DeepSeek beats on some rankings. The cost of training an American LLM is tens of millions of dollars and rising. DeepSeek’s owner says it spent under $6m.
American firms can copy DeepSeek’s techniques if they want to, because its model is open-source. But cheap training will change the industry at the same time as model design is evolving. China’s inauguration-day release was DeepSeek’s “reasoning” model, designed to compete with a state-of-the-art offering by OpenAI. These models talk to themselves before answering a query. This “thinking” produces a better answer, but it also uses more electricity. As the quality of output goes up, the costs mount.
The result is that, just as China has brought down the fixed cost of building models, so the marginal cost of querying them is going up. If those two trends continue, the economics of the tech industry would invert. In web search and social networking, replicating a giant incumbent like Google involved enormous fixed costs of investment and the capacity to bear huge losses. But the cost per search was infinitesimal. This—and the network effects inherent to many web technologies—made such markets winner-takes-all.
If good-enough AI models can be trained relatively cheaply, then models will proliferate, especially as many countries are desperate to have their own. And a high cost-per-query may likewise encourage more built-for-purpose models that yield efficient, specialised answers with minimal querying.
The other consequence of China’s breakthrough is that America faces asymmetric competition. It is now clear that China will innovate around obstacles such as a lack of the best chips, whether by efficiency gains or by compensating for an absence of high-quality hardware with more quantity. China’s homegrown chips are getting better, including those designed by Huawei, a technology firm that a generation ago achieved widespread adoption of its telecoms equipment with a cheap-and-cheerful approach.
If China stays close to the frontier, it could be the first to make the leap to superintelligence. Should that happen, it might gain more than just a military advantage. In a superintelligence scenario, winner-takes-all dynamics may suddenly reassert themselves. Even if the industry stays on today’s track, the widespread adoption of Chinese AI around the world could give the ccp enormous political influence, at least as worrying as the propaganda threat posed by TikTok, a Chinese-owned video-sharing app whose future in America remains unclear. (...)»
Chinese AI is catching up, posing a dilemma for Donald Trump
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