Fine Tuning Future
Jerry discusses the shift towards fine tuning in Lamindex's future, highlighting the benefits of optimizing workflows. He explores the potential competition between fine tuning and Rag approach, emphasizing the importance of user experience and capabilities in shaping the direction of development.In this clip
From this podcast
Unsupervised Learning
Ep 18: LlamaIndex CEO Jerry Liu on Trends in LLM Applications
Related Questions
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 Cohere co-founder Nick Frosst on building LLM apps for business and the clip Model Evaluation Insights?
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 and the clip Model Evaluation Insights?
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 and the clip Model Evaluation Insights?