How to Win at AI: Why Decentralization Can Help the US Avoid the Next DeepSeek Surprise
China's DeepSeek R1 model has highlighted contrasting innovation strategies between China and the United States in the AI landscape. Unlike the U.S., which often relies on patents and competitive secrecy, China embraces a culture of rapid iteration and collaboration, allowing for more resource-efficient solutions. DeepSeek is a lightweight AI model that successfully mimics the functionality of larger models while being significantly cheaper to use and train. This approach demonstrates the advantages of collective innovation and iteration over isolation in development. The success of DeepSeek suggests that the U.S. should adopt a decentralized approach to AI, overcoming the limitations of centralized research efforts that stifle innovation. The newly formed Decentralized AI Society (DAIS) is an initiative aiming to promote collaboration and knowledge sharing to drive technological advancements. As the AI field evolves, embracing decentralization may be key to avoiding future competitive shocks, where collective efforts can lead to accelerated improvements in technology.
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