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10 Challenges in Building RAG-Based LLM Applications

Agenda

Imagine a world where your custom LLM applications seamlessly adapt to the ever-changing landscape of knowledge. That’s where Retrieval-Augmented Generation (RAG) comes in. But building RAG applications isn’t all smooth sailing. Even though they bring benefits like better data control and clearer explanations, there are challenges along the way.

Join us for an enlightening live talk as we delve into the complexities of RAG-based LLM applications, exploring the top ten challenges developers encounter during implementation.

In this discussion, we will:

  • Learn about RAG’s pivotal role in shaping custom LLM applications, particularly in the realm of dynamic knowledge management.
  • Explore the multifaceted benefits of RAG, alongside the challenges and top implementation hurdles that developers often face.
  • Identify the ten most common challenges spanning both technical intricacies and governance concerns, providing invaluable insights into navigating these obstacles effectively.
  • Gain practical strategies and solutions for successful implementation of RAG-based LLM applications, equipping you with the tools needed to overcome challenges and achieve desired outcomes.

This session promises to offer actionable insights and strategies that will help you navigate the complexities of building RAG applications with confidence.

Raja Iqbal-Data Science Dojo
Raja Iqbal

CEO and Chief Data Scientist at Data Science Dojo

Raja Iqbal is a data scientist, a passionate educator, and an internationally recognized speaker on data science. Prior to Data Science Dojo, Raja worked at Microsoft in a variety of research and development roles involving machine learning and data mining at very large scale.

We are looking for passionate people willing to cultivate and inspire the next generation of leaders in tech, business, and data science. If you are one of them get in touch with us!