RAG Time: How Experts are Harnessing Retrieval-Augmented Generation

Are you curious about how Retrieval-Augmented Generation (RAG) is being used in natural language processing?

Retrieval-Augmented Generation is an emerging approach in NLP that combines the strengths of retrieval systems with generative models. It allows AI to pull relevant information from external datasets during text generation, improving the accuracy and relevance of responses in applications like chatbots and content generation. If you’re interested in exploring this technology further, don’t miss this engaging session where practitioners share real-world applications and insights.

Join us on September 20th, 2024 at 10 am ET, when our three featured speakers will walk us through their unique journeys and the lessons learned from implementing RAG in various contexts.

• Guillaume Soto will kick off the session with a presentation on developing a chatbot using RAG to access data from the Central African Forest Observatory (OFAC). He’ll discuss the hurdles and opportunities he encountered while working on this project.
• Maria Dyshel will bring her expertise to the table, focusing on key parameters that can enhance the relevance and accuracy of RAG applications. Her session promises actionable advice for improving the performance of RAG systems in different contexts.
• James Goh rounds out the speaker lineup with his findings on AI model evaluation, providing a forward-looking analysis of RAG’s place in the NLP toolkit given advancements in context window lengths and decreasing text input costs.

Beyond these focused case studies, we’ll dive into broader questions around RAG’s role in NLP:

• What are the most promising use cases for RAG models?
• How can you optimize RAG models given the technical and data availability constraints?
• What are the key benefits and limitations of using RAG, and will it remain relevant in future NLP advancements?

Register now for a stimulating discussion on the evolving landscape of Retrieval-Augmented Generation, exploring both its current challenges and its future potential in natural language processing. Whether you’re a seasoned AI professional or new to RAG technology, this event offers valuable insights and practical takeaways that can inform your own work.

To continue the conversation, we’re also hosting an interactive Slack chat for NLP-CoP Members following the session (currently scheduled for Monday, September 23rd — final date and time TBC), where attendees and speakers can dive deeper into the topics covered, ask follow-up questions, and network with fellow practitioners. Be sure to join the NLP-CoP and request to be added to our Slack if you’d like to keep the dialogue going!

Don’t miss this chance to connect with experts, learn from real-world applications, and explore the future of RAG in NLP! Register here to reserve your spot for this free webinar.