10 Challenges in Building RAG-Based LLM Applications

RAG stands at the forefront of custom LLM applications, providing solutions to the ever-changing landscape of knowledge. However, navigating its complexities is crucial.
Join us in our upcoming live talk, “10 Challenges in Building Retrieval Augmented Generation (RAG)”, as we explore the benefits, challenges, and top implementation hurdles of RAG-based LLM applications. Discover the ten most common challenges developers face, spanning technical intricacies and governance concerns, and gain practical strategies for successful RAG-based LLM implementation.
Key Takeaways:
- Learn about RAG's importance in custom LLM apps for dynamic knowledge
- Explore benefits, challenges, and top implementation hurdles
- Identify 10 common challenges, spanning technical and governance issues
- Gain practical strategies for successful RAG-based LLM implementation
Table of Contents:
00:00 Introduction
00:54 Stages in Naive RAG
16:42 Problems with Naive RAG
22:50 Data Ingestion
39:30 Pre-retrieval
43:11 Retrieval
52:50 Post-retrieval
56:49 Generation
--
💼 Learn to build LLM-powered apps in just 40 hours with our Large Language Models bootcamp: hubs.la/Q01ZZGL-0
👉 Learn more about Data Science Dojo here:
datasciencedojo.com/
👉 Watch the latest video tutorials here:
tutorials.datasciencedojo.com/
👉 See what our past attendees are saying here:
datasciencedojo.com/bootcamp/...
--
At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 8000+ employees from over 2000+ companies globally, including many leaders in tech like Microsoft, Apple, and Facebook.
--
🔗 Subscribe to our newsletter for data science content & infographics: datasciencedojo.com/newsletter/
---
#RAGChallenges #LLMApplications #AIImplementation #AIChallenges #artificialintelligence #rag #llm #largelanguagemodels #ai

[@MortaAriyano]

very informative lectures, thanks.

[@Datasciencedojo]

Thank you for the feedback!