Speakers
Bryan Wood
Machine Learning Solutions Engineer
Snorkel AI
Bryan is an accomplished Executive with over 15 years of experience in financial services, specializing in Artificial Intelligence and Data Strategy. Recognized for leading AI-driven innovations and managing large-scale projects that enhance business processes and compliance within complex regulatory frameworks. Proven in directing AI initiatives, developing strategic roadmaps, and fostering a culture of continuous improvement and technological adoption.
Enhancing RAG Pipelines for Enterprise-Specific Tasks: Strategies for Accuracy and Reliability
In the realm of LLM-powered AI applications, Retrieval-Augmented Generation (RAG) is a pivotal component for enterprise use cases. However, to ensure responses are consistently accurate, helpful, and compliant, RAG pipelines must undergo meticulous optimization.
Critical to this process is the incorporation of only the most relevant information as context. This can be achieved through techniques such as semantic document chunking, fine-tuned embeddings, reranking models, and efficient context-window utilization.
In this presentation, we will:
- Introduce fundamental RAG concepts and outline a standard pipeline.
- Detail optimization strategies for each stage of a sophisticated RAG pipeline to ensure the LLM receives proper context.
- Demonstrate how to leverage Snorkel Flow to optimize RAG pipelines.
By attending, you will gain insights on how to:
- Enhance LLM responses by minimizing retrieval errors.
- Fine-tune various stages of the RAG pipeline.
- Expedite the deployment of production-grade RAG applications.
Join us to elevate your RAG systems and drive superior AI outcomes for your enterprise.