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Decentralized AI networks are seeking to build distributed computing infrastructure that uses smartphones as computing resources.
The model would connect hundreds of thousands of smartphones to handle AI computing workloads, pursuing an infrastructure different from traditional centralized data centers.
It remains uncertain whether the model can secure the stability and cost efficiency needed for large-scale AI services, and further validation is required.
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Decentralized artificial intelligence networks are seeking to build distributed computing infrastructure that uses smartphones as computing resources. It remains unclear, however, whether the model can provide the stability and cost efficiency needed for large-scale AI services.
Cointelegraph reported on Nov. 5 that decentralized AI networks are exploring ways to connect hundreds of thousands of smartphones to process AI workloads.
The approach links the computing power of individual smartphones into a network for AI tasks. Unlike traditional centralized data centers, it uses dispersed devices as computing infrastructure.
Even if hundreds of thousands of smartphones are connected, it has yet to be proven whether the system can reliably run large-scale AI services while remaining cost-competitive.
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