Meta Fiberverse: Towards Symbiotic Edge Intelligence with Fabric Computing and LLMs

With the development of ubiquitous computing and multimodal sensing, intelligent terminals are evolving towards a “human-machine symbiosis” paradigm, increasing demands for intelligent, autonomous and self-adaptive terminal systems. However, existing systems still face fun-damental challenges in real-world deployments: 1) trade-off between user comfort, data fidelity, and privacy; 2) absence of context-aware scheduling mechanisms; and 3) limited capabilities in semantic generalization. To address these challenges, we propose Meta Fiberverse, a fabric-based computational platform designed for human-machine-environment symbiosis. The system integrates high-density fabric sensing, high-fidelity scheduling mechanisms, and plugin-enhanced semantic coordination framework powered by large language models. Experimental results demonstrate the system’ s performance in communication latency and task accuracy, offering a feasible path and technical reference for next-generation human-centered intelligent terminals with human-machine symbiosis, resource self-consistency, and semantic autonomy.

Authors

Publication Details

Journal
Tsinghua Science & Technology
Published
2026-04-01
DOI
https://doi.org/10.26599/tst.2025.9010176
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Meta Fiberverse: Towards Symbiotic Edge Intelligence with Fabric Computing and LLMs

Guangming Tao, Xiao-Kun Wu, Salman A. AlQahtani, Yue Wang et al.
Tsinghua Science & Technology
IoT and Edge/Fog Computing
article

Meta Fiberverse: Towards Symbiotic Edge Intelligence with Fabric Computing and LLMs

Guangming Tao, Xiao-Kun Wu, Salman A. AlQahtani, Yue Wang, Lejun Ai, Gang Wei, Wenjing Xiao, Jia Liu, Min Chen
article en

Abstract

With the development of ubiquitous computing and multimodal sensing, intelligent terminals are evolving towards a “human-machine symbiosis” paradigm, increasing demands for intelligent, autonomous and self-adaptive terminal systems. However, existing systems still face fun-damental challenges in real-world deployments: 1) trade-off between user comfort, data fidelity, and privacy; 2) absence of context-aware scheduling mechanisms; and 3) limited capabilities in semantic generalization. To address these challenges, we propose Meta Fiberverse, a fabric-based computational platform designed for human-machine-environment symbiosis. The system integrates high-density fabric sensing, high-fidelity scheduling mechanisms, and plugin-enhanced semantic coordination framework powered by large language models. Experimental results demonstrate the system’ s performance in communication latency and task accuracy, offering a feasible path and technical reference for next-generation human-centered intelligent terminals with human-machine symbiosis, resource self-consistency, and semantic autonomy.

Tsinghua Science & Technology
Openalex Percentile: Top 17%
IoT and Edge/Fog Computing
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