In this episode, I chat about rerankers and representation models with Sylvie Shi, Rerank Team Lead at Cohere. We cover the essentials of non-generative large language models, focusing on how reranking and representation models are upgrading search and advanced RAG systems. Sylvie shares her journey into machine learning and her work on semantic search and rerankers. We chat about common use cases, good practices, and potential pitfalls when using reranking models, highlighting their application in advanced RAG systems. Guide On How To Build Advanced RAG With Command R+ and Rerank: https://cohere.com/blog/rag-chatbot  Text Representation, Embeddings, Reranking - LLM University course resources: https://docs.cohere.com/docs/intro-large-language-models  https://docs.cohere.com/docs/intro-text-representation  https://docs.cohere.com/docs/intro-semantic-search  https://docs.cohere.com/docs/reranking-2 Reranking Best Practices: https://docs.cohere.com/docs/reranking-best-practices Learn more about Rerank 3: https://cohere.com/blog/rerank-3 Try it out: https://docs.cohere.com/docs/rerank-2  Watch all the episodes on YouTube: https://www.youtube.com/playlist?list=PLhBwB1lBTwJWR19WkJw87EMh1JU9O7Uff I'm a co-author of a manual on GPT-3 and OpenAI API (Packt, 2023): https://www.packtpub.com/product/gpt-3/9781805125228 You can keep in touch with me via socials: IG, TikTok, X, LinkedIn @itsSandraKublik Sign up for my Substack newsletter for the personal scoop on the topics covered today: https://substack.com/@itssandrakublik  Website: www.sandrakublik.com For brand collabs, reach out to me at [email protected] Music by: Acid Jazz by Kevin MacLeod is licensed under a Creative Commons Attribution 4.0 license. https://creativecommons.org/licenses/by/4.0/

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