This study systematically applies parameter-efficient fine-tuning (PEFT) using Low-Rank Adaptation (LoRA) to Qwen2.5-3B for a telecommunications customer support conversational assistant. It evaluates 16 LoRA configurations, varying hyperparameters and target modules, using a combinatorial synthetic data generation approach.
This work proposes a neural network-based approach to predict customer churn in cellular network services. The objective is to identify user behavior patterns to anticipate service abandonment.
Azercell Telecom partnered with the AWS Generative AI Innovation Center to develop an Azerbaijani large language model (LLM) on Amazon SageMaker AI. This six-week collaboration established a production-ready framework for telecom use cases and a customer-facing chatbot, overcoming data scarcity and linguistic complexity challenges.
The telecommunications industry faces increasing demands for connectivity, pushing traditional operational models to their limits. Agentic AI tools are transforming this sector by independently acting, coordinating systems, and optimizing network operations in real-time, moving beyond rule-based automation.
This excerpt from "The Download" newsletter reports on a new US-wide cell phone network marketed to Christians. Set to launch next week, it aims to block pornography and gender-related content.