Open data is key to a $350 billion emerging tech economy but often relies on centralized infrastructure, which contradicts the principles of Web3. To optimize the potential of open data, a transition to decentralized infrastructure is essential. This shift can enhance user application security and reduce costs, particularly when training large language models (LLMs). The centralized AI model systems incur high expenses, contrastively, decentralized platforms can leverage cheaper computing resources. Furthermore, decentralization fosters more accessible research data sharing, bypassing the costly journal systems that limit access, while also ensuring privacy through blockchain technology. Current centralized hosting platforms like AWS and Google Cloud present single points of failure; decentralized solutions could provide more robust reliability. Incorporating decentralized protocols can streamline application development and adaptability in the burgeoning Web3 environment. Overall, a pivot to decentralized infrastructure will solidify the growth of open data, keeping in line with Web3's vision of autonomy and resistance to censorship.

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