Enhanced Anomaly Detection with LLMs for Telecommunications Networks
Anomaly detection has been a staple in network monitoring and operations for over a decade.
The ability to identify a meaningful change in network behavior, as early as possible, has been a subject of much research, development, and application. In this episode of AI for Telecommunications, in partnership with Deepsense.ai, and our sister company Reailize, we share our most recent findings on how LLMs can be used to improve anomaly detection, reduce alert fatigue, and enhance network operations efficiency.
By watching this webinar, you'll learn the following:
- The vital role of anomaly detection in network monitoring and its evolution over the years.
- Techniques to identify meaningful changes in network behavior and differentiate between Data vs. Network Anomalies promptly.
- How LLMs (Large Language Models) amplify the efficiency of anomaly detection.
- Strategies to reduce alert fatigue and ensure actionable insights.
- Collaborative findings from industry leaders: deepsense.ai, Reailize, and B-YOND.
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About the Speakers
Mateusz Wosiński, Senior Data Scientist at deepsense.ai - Having spent the last years specializing in advanced AI projects, he brings a well-rounded approach to Machine Learning (ML), engaging with a wide range of topics around Computer Vision and Natural Language Processing. Mateusz enjoys pushing the envelope and is an active contributor to the ongoing experiments with Large Language Models both from the perspective of business and the ML community.
Agustin Johnson, Telecom Engineer at Reailize - has 18+ years of experience in mobile network operations, including deployment, integration, monitoring, and assurance areas.
He has led different programs that transformed network operations by introducing automation and AI/ML solutions, increasing their efficiency and placing the customer in a central role. As a Solution Architect at Reailize, Agustin serves as a domain expert and advisor to Mobile Network Operators, overseeing their solution roadmap, translating improvement opportunities into automation requirements and making sure the right tools and processes are implemented.
Anand Ravi, Lead Architect at B-YOND - holds a Master's degree in Telecommunications, and has over a decade of hands-on experience in network testing and operations. Anand is an expert in 5G network troubleshooting and packet analysis.
