Fig. 2: Comparison between conventional cloud-centric approach and ubiquitous intelligence approach.
From: Ubiquitous intelligence via wireless network-driven LLMs evolution
In the traditional approach, all data and computation are routed through centralized cloud infrastructure, leading to latency, privacy risks, and limited personalization. The ubiquitous intelligence framework leverages BSs, access points, and edge devices as active intelligence nodes, enabling local inference, cooperative learning, and D2D knowledge sharing. The distributed structure supports low-latency adoption and enhances resilience and personalization in dynamic wireless environments.
