Network Artificial Intelligence, Fast and Slow

被引:2
作者
Rossi, Dario [1 ]
Zhang, Liang [2 ]
机构
[1] Huawei Technol Co Ltd, Paris, France
[2] Huawei Technol Co Ltd, Nanjing, Peoples R China
来源
PROCEEDINGS OF THE 1ST INTERNATIONAL WORKSHOP ON NATIVE NETWORK INTELLIGENCE, NATIVENI 2022 | 2022年
关键词
AI Native Networking; Machine Learning; Artificial Intelligence;
D O I
10.1145/3565009.3569521
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As networks have historically been built around connectivity, architectural features concerning quality of service, mobility, security and privacy have been added as afterthoughts with consequent well known architectural headaches for their later integration. Despite Artificial Intelligence (AI) is more a means to an end, that an architectural feature itself, this is not completely different from what concerns its integration: in particular, while Cloud and Edge computing paradigms made it possible to use AI techniques to relieve part of network operation, however AI is currently little more than an additional tool. This paper describes a vision of future networks, where AI becomes a first class commodity: its founding principle lays around the concept of "fast and slow" type of AI reasoning, each of which offers different types of AI capabilities to process network data. We next outline how these building blocks naturally maps to different network segments, and discuss emerging AI-to-AI communication patterns as we move to more intelligent networks.
引用
收藏
页码:14 / 20
页数:7
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