Build RAG-based large language model applications with Ray on Google Kubernetes Engine
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Published on ● Video Link: https://www.youtube.com/watch?v=YU8yIyuFeJo
0Large Language Models (LLMs) have changed the way we interact with information. A base LLM is only aware of the information it was trained on. Retrieval augmented generation (RAG) can address this issue by providing context of additional data sources. In this session, we’ll build a RAG-based LLM application that incorporates external data sources to augment an OSS LLM. We’ll show how to scale the workload with distributed kubernetes compute, and showcase a chatbot agent that gives factual answers.
Speakers: Kai-Hsun Chen , Winston Chiang
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