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QPD // Career Tutorial on LLMs for all Expertise Levels

 

— with Dr. Mathis Börner (Senior Data Scientist, SAP)

Retrieval-Augmented Generation (RAG) – our lifeguard and savior for hallucination in Large Language Models? Beginning with fundamental concepts of LLMs and in-context learning, we’ll address the “Needle in the Haystack Problem” and compare ultra-long context models with RAG approaches. Through practical demonstrations, participants will gain hands-on experience with RAG’s core functionalities and understand its objectives. The session delves into scaling solutions using vector databases and advanced implementations, including chunking strategies, hybrid RAG, and graph-based RAG architectures. We conclude with an overview of emerging trends, examining agentic RAG and the integration of reasoning models in deep research applications. This comprehensive exploration equips attendees with both theoretical knowledge and practical insights into the latest developments in AI language models.

When: March 7, 2025, 9 am – 3 pm
Where: WI Flexroom (A1_04); hybrid
Level: Beginner/Intermediate/Advanced
Seats: 20 (in-person); no limit (online)

Registration deadline: March 6, 2025

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