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Serenity tweeted about the phenomenon of U.S. companies’ heavy reliance on Chinese AI models, citing a UBS report that many enterprises have begun routing simple tasks to cheaper Chinese open-source models. Some teams spend up to $35,000 monthly on tokens—200% over budget—putting pressure on high-end AI model revenue growth. Serenity deemed the UBS report accurate, attributing the trend to a capitalist dilemma: markets naturally gravitate toward the cheapest option, and Chinese models like DeepSeek are significantly cheaper than those from Gemini, OpenAI, and Anthropic. Serenity also stated that the Trump administration’s earlier pause on access to Fable/Mythos was the right move, as repeated distillation of top-tier models poses enormous risks, and models approaching ASI-level should have higher access barriers. The expert noted that the U.S. needs two key actions: further develop models specialized in low-cost inference, and impose bank-grade identity authentication for AI model access.
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