Definition ∞ Decentralized inference refers to the process of executing machine learning model predictions across a distributed network of computational nodes rather than on a single, centralized server. This approach aims to enhance privacy, reduce reliance on central authorities, and improve fault tolerance. Participants in the network contribute computational resources to process data and generate outcomes. It offers a more robust and censorship-resistant method for data analysis.
Context ∞ Decentralized inference is a developing concept at the intersection of artificial intelligence and blockchain technology. In crypto news, it appears in discussions about protocols aiming to provide AI services without centralized control, leveraging decentralized networks for data processing. This method seeks to address concerns about data ownership and the concentration of power in large AI companies. Its implementation could alter how AI models are deployed and utilized within web3 ecosystems.
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