HUANG Yangkun ZHU Hongyu CHEN Changfeng
2025, 47(6): 137-158.
This paper empirically explores the access of large language models (LLMs) on a global
scale, to examine their infrastructuralization and dilemmas towards general AI. Drawing upon the
basic idea of connectivity from communication and media studies, and adopting “gateway” as the
core concept of infrastructure, this study employs computer network experiments as the primary
method and utilizes indicators including packet loss, latency, and jitter to examine the global
access conditions including accessibility, speed, stability of LLMs as new digital infrastructure
along with the potential inequality issues behind them. Through conducting nearly 200,000
network probes across 62 global network nodes, this study finds that compared to city nodes in
the Global North, city nodes in the Global South generally exhibit a disadvantage in terms of
accessibility, especially when accessing LLMs produced in Western countries. Furthermore, some
LLMs have significantly surpassed “old-type” information infrastructures like search engines and
databases in terms of accessibility and speed, with nodes in the Global South accessing LLMs
notably faster than databases. However, LLMs have not yet demonstrated a significant superiority
in stability over previous-generation information infrastructures. Although the emergence of
LLMs metaphorically signifies a primary stage of global information exchange and human-
machine interactions, it is still imperative to address and resolve geopolitical conflicts within
connectivity. Addressing the factors like access, usability, stability, universalisation and value will be crucial for LLMs to realize their full potential and evolve into global gateways.
