币界网报道：The development strategy of Web3AI should avoid simply imitating the Web2 model, but take a differentiated path. The core challenge currently faced by Web3AI is the semantic alignment problem of multimodal models, that is, how to map different forms of data such as images and texts to a unified semantic space. Compared with the mature cross-modal conversion mechanism of Web2AI, the semantic alignment efficiency under the flat architecture of Web3 still needs to be improved, which directly affects the performance of the system. Experts suggest that Web3AI should adopt a gradual development strategy of "surrounding the city with the countryside", focusing on breaking through key technical bottlenecks such as high-dimensional space semantic alignment, attention mechanism optimization, and heterogeneous computing power coordination.