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SYSTEM AND METHODS FOR SELF-LEARNING MANAGEMENT OF NEXT GENERATION NETWORKS

发明专利审中
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20权利要求 · 3 独立
§ Ⅰ

卷宗概要

发明人

Mark Stockert; Jerry Robinson; Vijay Bhaskar Uppala; Joseph Dahan

IPC 分类

H4L 41/4H4L 9/8H4L 41/897

CPC 分类

H4L41/4H4L9/852H4L41/897

Aspects of the subject disclosure may include, for example, a system including: one or more probes in a communication network; a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: collecting data from the one or more probes and application program interfaces of network elements in the communication network; converting the data into semantic vectors using an embedding model; storing the semantic vectors in a vector database; using foundation models to generate outputs based on the semantic vectors; generating synthetic data using a generative adversarial network, wherein the synthetic data is used test the foundation models; using federated reinforcement to incorporate human feedback into the semantic vectors; and managing the communication network based on the outputs. Other embodiments are disclosed.

原文(中文)

Aspects of the subject disclosure may include, for example, a system including: one or more probes in a communication network; a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: collecting data from the one or more probes and application program interfaces of network elements in the communication network; converting the data into semantic vectors using an embedding model; storing the semantic vectors in a vector database; using foundation models to generate outputs based on the semantic vectors; generating synthetic data using a generative adversarial network, wherein the synthetic data is used test the foundation models; using federated reinforcement to incorporate human feedback into the semantic vectors; and managing the communication network based on the outputs. Other embodiments are disclosed.