Monday, 31 March,
14:00
–
18:30
Rooms 201-202 (Level 2)
Generative AI is revolutionizing the telecommunications industry, enhancing network operations and performance monitoring through capabilities like text, image, video, and code generation, as well as intelligent search and reasoning for autonomous agents. The outcomes from real-time data analysis, anomaly detection, predictive maintenance, network planning and optimization based on physical layer measurements, when efficiently used by AI, can further aid to achieve the vision of network automation. These advancements boost efficiency and productivity in network operations. However, concerns around cost, performance, and data accessibility, as well as security, privacy, and compliance issues, complicate the deployment process.
This session invites participants to explore generative AI use cases in telecommunications and AI-enhanced performance monitoring, addressing obstacles in transitioning from proof of concept to production. We will focus on the following topics:
- Generative AI in Telecom: Applications for network operations, digital twins, capacity planning, and other use cases.
- AI-Enhanced Performance Monitoring: Real-time data analysis, anomaly detection, predictive maintenance, and network planning and optimization.
- Performance Monitoring at Physical Layer: Novel methods for performance monitoring including power profile estimation with coherent signal processing, polarization sensing, distributed sensing or combinations thereof.
- Tools and Collaboration: Open-source models, generative AI techniques (e.g. RAG), inter-vendor applications, and partnerships between vendors, operators, and AI companies.
- Data and Security: Data governance, security, privacy, and responsible AI & model evaluation.
First Session
Larry Zhou, ATT, USA
Generative AI applications in Telecom
Imen Grida Ben Yahia, AWS, UK
Generative AI for Network Operations
Anurag Sharma, Google, USA
AIOps: The Autonomous Network Journey
Cen Wang, KDDI Research, Inc., Japan
LLM-centric Transport Network Configuration Management Framework and Demonstration
Harish Babu Arunachalam, Verizon, USA
Measuring and Mitigating Generative AI Risk: Successes and Challenges from a Practitioner Perspective
Christopher Janz, Huawei, Canada
Operations Science and Automation in Optical Networks: From Machine Learning to Generative AI
Second Session
Seb Savory, Univ. of Cambridge, UK
Machine Learning Based Physical Layer Monitoring
Zhiping Jiang, Huawei Technologies, Canada
New Performance Monitoring Capabilities at Physical Layer
Takeo Sasai, NTT, Japan
Design Principle of Fiber-Longitudinal Power Monitor
Inwoong Kim, Fujitsu Network Communications, USA
Digital Twin Optical Networks Aided by DSP-based Longitudinal Power Profile Monitoring
Ming-Fang Huang, NEC Laboratories, USA
Generative AI for Distributed Acoustic Sensing Event Classification in Telecom Networks
Matheus Sena, Deutsche Telekom AG, Germany
Beyond Optical Layer Monitoring: Exploring the Full Potential of Coherent Signal Processing