Innovative Strategies for Applying LLMs in Telecom
This webinar explores the transformative potential of Large Language Models (LLMs) in the telecommunications industry.
Discover how LLMs can revolutionize the way data is generated, enabling businesses to create innovative strategies and optimize their services.
The importance of LLMs and their potential impact on the telecommunications industry
The role of LLMs in data generation and the type of transfer learning they employ
Real-world use cases and current approaches to implementing LLMs in telecommunications
Practical steps to effectively implement LLMs in your business or organization
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About the Speakers
This webinar features experts Nathanael Weill, Director of Data Science at B-Yond and Jan Milzcek, Principal Data Scientist at deepsense.ai.
Nathanael Weill is a Director of Data Science with expertise in productization using big data solutions and machine learning algorithms. He currently leads three teams of data scientists at B-Yond, which provides AI-powered software for packet capture analysis and diagnosis. Nathanael previously held similar positions at CGI and LANDR, where he developed products using machine and deep learning algorithms for audio processing, recommendation systems, and more. Nathanael is also a lecturer at McGill Continuing Study, where he has been teaching in the Data Science Certificate program since 2018. Nathanael is committed to working closely with customers and developing new prototypes using design thinking methodology.
Jan Kanty Milczek is a Principal Data Scientist and one of the founding members of deepsense.ai. He specializes in applying data structures and algorithms in artificial intelligence. His current work focuses on improving and extending modern models with simulated annealing. He has won multiple data science competitions, including NOAA’s Whale Recognition – cited by Andrej Karpathy as an example of AI influencing the world for the better. He is actively engaged in the artificial intelligence community. As a speaker at data science conferences, he delivers presentations and participates in panel discussions on various AI-related areas, contributing to the ongoing practical and theoretical development of the field.