Enhance LLMs with RAG and Accelerate Enterprise AI with Pure Storage and NVIDIA

The benefits and ROI of Generative AI for enterprises are clear with retrieval-augmented generation (RAG). RAG provides company-specific responses by enhancing generic large language models (LLMs) with proprietary data. 

This session will show how an enterprise implementation of RAG with Pure Storage® and NVIDIA speeds-up data processing, increases scalability, and provides real-time responses more easily than creating custom LLMs from scratch. 

Attend to get technical insight and see a demonstration of distributed and accelerated GenAI RAG pipelines.

• Learn the benefits of enhancing LLMs with RAG for enterprise-scale GenAI applications

• Understand how to accelerate the RAG pipeline and deliver enhanced insight using NVIDIA NeMo Retriever microservices and the Pure Storage FlashBlade//S™

• See our proof of concept demonstration, showing accelerated RAG in an enterprise use case