Technology

The article discusses the concept, application directions, and related cryptocurrency projects of decentralized computing. Decentralized computing mainly involves processing data to output results, with its biggest market demand being AI training. Despite facing technical challenges such as data synchronization, network optimization, and data privacy and security issues, decentralized computing holds tremendous potential in the field of AI.

Bittensor, Fetch.ai, and SingularityNET share a common goal: using token incentives to drive the supply of AI resources, whether models, compute, or services, while building open networks that lower barriers to AI access and challenge the dominance of centralized platforms. However, their core differences lie in the technical layers they operate on and how they capture value. Rather than competing within a single track, they address three distinct stages of decentralized AI, model production, task execution, and service distribution.