Retrieval Augmented Generation (RAG) has taken the generative AI world by storm. By combining vector databases and large language models, RAG has become the de facto way to search and navigate enterprise data for generative AI. Watch Douwe Kiela, the inventor of retrieval augmentation, in a fireside chat with DataStax to discuss the origins of RAG, and where it is going. We cover specific advanced topics such as multimodal models and fine-tuning with RAG.

We explore Gen AI hot topics like:

Where did RAG come from and what’s next
Multimodal models and fine-tuning with RAG
Foundation models and the success over at Contextual AI