Exploring Generative AI Use Cases in Telecom and Open Source Models
summary
Discusses applying large language models in telecom for log anomaly detection and root-cause analysis of network health, improving customer experience via camera/microphone signals, and accelerating developer productivity with foundation models. Compares full model training to fine-tuning and retrieval-augmented inference (language chains) for frequently changing knowledge, and outlines a stack with large-scale compute, hybrid storage/network and edge optimizations while recommending shared baseline models, operator-provided training data and strict compliance, licensing, security and privacy controls.
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chapters (6)
- 0:00Generative AI in telecom
- 3:28AI in telecom networks
- 6:20LLM evolution and selection
- 12:24ZT Solutions AI architecture
- 14:28Telecom-AI collaboration
- 16:24Q&A
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