Cost moat or commons? DeepSeeks cut costs by 99%, where will the US giant’s trillion-dollar bet go?
When open-weighted models such as DeepSeek cut AI costs by 99%, U.S. capital’s trillion-dollar bet based on monopoly assumptions faces a fundamental challenge—AI capabilities are being commoditized.
Cost moat or commons? The AI industry landscape after DeepSeek cut costs by 99%
The underlying logic of US capital funding AI is based on the assumption of a "monopoly moat" - companies with the most advanced models will gain an insurmountable competitive advantage. But when open weight models such as DeepSeek cut AI costs by 99%, does it still make sense to invest hundreds of billions of dollars in building a "moat"? This is a core proposition that is fundamentally shaking the global AI industry landscape.
The core contradiction is: if AI capabilities can be copied and deployed at a cost of 1/100 or even 1/1000, price competition will inevitably compress the profit margins of all participants, and the industry may fall into a "tragedy of the commons" - everyone can obtain advanced AI capabilities at a very low cost, but no one can obtain excess returns from it.
The deeper problem is: U.S. export controls on China have accelerated China’s independent innovation in the field of AI. DeepSeek is the perfect footnote to this paradox—control attempts to restrict China’s access to advanced computing power, but it has inspired China to make breakthroughs in algorithm efficiency and cost optimization, ultimately impacting the U.S. market with lower prices.
The analytical framework of "moat vs. commons" accurately describes the core tension in the current global AI industry: closed-source giants are trying to build technology monopolies, while open-source/open weight models are turning AI capabilities into public resources. As the standard bearer of this "commercialization" movement, DeepSeek's subsequent trend will directly affect the global AI industry pattern.
For China’s AI industry, this is both an opportunity and a warning. Commodification means huge market share potential, but it also means continued compression of profit margins – how to build a sustainable business model at low prices is a question that all Chinese AI companies must answer.
Directions worthy of follow-up:
- Business model evolution: Under the trend of commoditization, how can AI companies build differentiated profit paths?
- The counter-effects of export controls: Do controls continue to accelerate China’s independent innovation as stated in the analysis?
- Industrial Pattern Reshaping: How much market share can the open source/open weight model ultimately occupy?
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