Founders and Futurists
Reducing LLM Hallucinations with Retrieval Augmented Generation: A Conversation with Ofer Mendelevitch In this episode, Joshua Schoen of Work AI discusses the complexities and innovations in the field of Retrieval Augmented Generation (RAG) with Ofer Mendelevitch from Vectara. They delve into topics such as the importance of accurate data feeding to Large Language Models (LLMs) to reduce hallucinations, the capabilities of vector databases, and how Vectara provides a comprehensive RAG-as-a-Service solution. Offer also shares his journey from working with early GPT models to co-founding Vectara. They explore various use cases for Vectara's technology in legal, healthcare, and other sectors, and end with a demo showcasing the practical applications of RAG in legal document management. 00:00 Introduction to AI and Hallucinations 01:29 Offer's Journey with GPT and Syntegra 02:42 Joining Vectara and Its Mission 03:06 Vectara's Growth and Funding 03:31 What is Vectara? 06:54 RAG vs. Fine-Tuning 09:30 Reducing Hallucinations with RAG 12:39 Building a RAG Pipeline with Vectara 14:45 Customer Use Cases and Future of LLMs 18:51 Live Demo of Vectara's Capabilities 22:00 Conclusion and Final Thoughts This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit workingitwithai.substack.com [https://workingitwithai.substack.com?utm_medium=podcast&utm_campaign=CTA_1]
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