{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/966b1dd52bf348eaaa02f08ceb9bd526\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/966b1dd52bf348eaaa02f08ceb9bd526-dd61e969f67a80ab.gif","duration":6037.0879,"title":"Understanding Retrieval Augmented Generation 🚀","description":"In this video, I dive into the concept of Retrieval Augmented Generation (RAG) and its applications, particularly in the context of AI and data processing. I discuss how we can utilize various models and databases to enhance our search capabilities and improve the relevance of results. I also touch on the importance of understanding the underlying algorithms, like Google's re-ranking algorithm, and how they impact our work. Please take a moment to review the slides linked in the chat for additional context."}