Etzard Stolte | Global Head Of Knowledge Management Ptd

Etzard Stolte, Global Head Of Knowledge Management Ptd, Roche

Etzard leads the global Information / Knowledge Management effort in Pharma Manufacturing for F. Hoffmann-La Roche, with a focus on processes and tools for effective knowledge utilisation. An active customer base of 20k colleagues utilises a range of AI/NLP capabilities that improve knowledge flow and automate text based activities. High impact use-cases deliver document filing, activity sharing and automated insight generation. Etzard has worked at the interface of the Life- and Computer-Sciences for more than 20 years, in technical, managerial as well as strategic roles. Before joining Roche, Etzard worked as CIO at the Jackson Lab (a US based genomics research institutes), and was CTO for the Life Sciences at Hewlett Packard (a large technology vendor). Etzard has earned academic degrees in Biology, Bio-Informatics and Informatics, with a PhD in Computer Science from ETH Zurich on "A Scalable Architecture for Scientific Databases”.


Day 1 (26th June) @ 12:00

LLMs in the real (pharma) world

Large Language Models accelerates the way we process our knowledge in Pharma. Retrieval Augmented Generation (RAG) is the method of choice to automatically feed relevant content into LLM prompts. Yet, by default the quality of results is often poor, and a wide range of approaches is used to improve quality in real-world RAG systems, such as, prompt engineering, refinement training, fast NLP pipelines, KG/MD enrichment, specialised encoders, chunking strategies, etc. In this presentation, I will share some best-practice we learned while adding natural language queries using LLMs to a mature semantic search platform with 100 million records from 60+ systems, used by 20k users in Roche. Over the past years, some surprising insights have been learned during the implementing of this real-world RAG.

last published: 17/Jun/24 14:15 GMT

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