Making Retrieval Augmented Generation Better with

Join, Pinecone Developer Advocate, ‪@jamesbriggs‬ as he delves into retrieval augmented generation (RAG) and explores its role in enhancing Large Language Models (LLM) and chatbot applications. In this webinar, we'll explore the nuances RAG, the different ways that it can be applied, and the impact of each approach for augmenting language models and revolutionizing the capabilities of chatbots. This will provide a holistic understanding of how RAG can serve as a transformative force in GenAI.
James will also share invaluable insights into the intricacies of data preparation for RAG. Unearthing hidden gems in your dataset and optimizing it for retrieval augmentation is a crucial step in harnessing the full potential of this technology. You can expect to gain practical tips and tricks that will empower you to curate data that aligns seamlessly with your RAG pipelines.
👉 Slides: docs.google.co...

[@vikassalaria24]

Great video James.Since a year I am following you.Your content is simply awesome

[@jamesbriggs]

glad to hear!

[@kevon217]

Great discussion questions. All ones I’ve pondered as well. Appreciate sharing the webinar!

[@jamesbriggs]

there were plenty of great questions at this one!

[@micbab-vg2mu]

Great presentation - Thank you

[@jamesbriggs]

glad you enjoyed

[@dahiruibrahimdahiru2690]

Awesome webinar! I asked a question but unfortunately there wasn't time to get to it.
Here goes: If I had a query that requires document level knowledge like "what is the highest monetary value mentioned in the document", how should I approach that?

[@Stateset]

Thanks James

[@jamesbriggs]

you're welcome :)

[@lionhuang9209]

where can we download the ppt for the talk?

[@jamesbriggs]

here it is:
docs.google.com/presentation/d/1JCS9KPVhfLPHUMt9gLawMdT8t8xAoKij_zc5APy3F28/edit?usp=sharing

[@lionhuang9209]

Thanks very much for the link.@@jamesbriggs