The AI-Model Network: Concept, Current State, and Future Directions
arXiv:2606.27382 (cs.AI)
Submitted on 25 May 2026
Authors: Li Zhetao, Zeng Xiyu, Wang Jianhui, Xiao Yong, Liu Zhongren, Wu Junru, Lai Junjie, Huang Jijun, Long Saiqin
Abstract
While computers are fundamentally built for computation and processing, the Internet's core value lies in sharing and collaboration. Computers created the Internet, and the Internet magnifies the value of computers. The rapid evolution of the Internet, cloud computing, and big data has propelled artificial intelligence into the era of large models (LMs). However, as of 2026, the practical deployment of large models faces significant hurdles—primarily high training costs and complex infrastructure requirements. These challenges are driving a shift toward lightweight, private, and domain-specific models.
With the rapid proliferation of heterogeneous models across different platforms and organizations, enabling effective interaction and collaboration among them has become a critical bottleneck. Drawing inspiration from the development of the Internet, this paper proposes the concept, vision, and system architecture of a worldwide AI-Model Network (AI-ModelNet). This novel paradigm aims to achieve interconnection, capability sharing, and collaborative reasoning by establishing direct pathways between models.
We first briefly review the current state of single-model and multi-model research. Next, we articulate the systemic vision and hierarchical architecture of AI-ModelNet, and validate the framework's feasibility through a prototype system and diverse application cases. Finally, we discuss key directions for future research, highlighting areas such as model interoperability standards, security protocols, and decentralized AI coordination—all of which are expected to gain prominence by 2026 and beyond.
Paper Details
- Comments: 31 pages, 14 figures
- Subjects: Artificial Intelligence (cs.AI)
- MSC Classes: 68T01
- ACM Classes: C.0
- Cite as: arXiv:2606.27382 [cs.AI]
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