Retrieval and Generation
The discussion delves into the dual role of retrieval in enhancing generative processes. It explores how retrieval can either enrich generation with additional data or serve as a foundational knowledge store for making informed inferences. The interplay between these approaches highlights the importance of data in shaping AI outputs.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Mixture-of-Experts and Trends in Large-Scale Language Modeling with Irwan Bello - #569
Related Questions
Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data?
Do I understand correctly that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data, as discussed in the episode with Cohere co-founder Nick Frosst on building LLM apps for business?
Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data, as discussed in the episode with Cohere co-founder Nick Frosst on building LLM apps for business?