Building Performant AI Applications with NVIDIA NIMs and Haystack
Date and Time:
September 04, 2024, 8 am PST, 11 am EST, 5 pm CEST
During this session, we’ll show you how to use deepset’s Haystack framework and NVIDIA NIM to build and deploy a compound AI application that can run on-prem as well as in cloud native environments.
First, you’ll learn some basics about NVIDIA NIM, which is a collection of containerized microservices designed for optimized inference of state-of-the-art AI models.
We’ll follow that with a live coding demonstration of building a RAG application with Haystack.
Then we’ll show you how to deploy this application with Kubernetes and scale it up. Finally, there will be plenty of time to answer your questions at the end.
You’ll leave with not only a better understanding of how to build and scale AI applications, but 1000 free NVIDIA inference requests, so you can try out different models for yourself.
Sign up below to attend live. We'll send a recording of the webinar to all registrants after the session.
Speakers:
Tuana Çelik
Lead Developer Relations Engineer - deepset
Tuana is the Lead Developer Relations Engineer at deepset for Haystack. She helps the AI community understand how to build reliable RAG applications with Haystack and our technology partners. She’s based in Amsterdam, Netherlands.
Mark Moyou
PhD. Sr. Solutions Architect – NVIDIA
Dr. Mark Moyou is a Senior Data Scientist at NVIDIA on the Retail team working with North Americas top Retailers on scaling ML workloads. On the side, Mark is the host of the AI Portfolio Podcast, Caribbean Tech Pioneers Podcast and the Optimized AI Conference in Atlanta.
Anshul Jindal
Senior Solution Architect - Cloud Services at NVIDIA
Anshul is a Sr. Solution Architect at NVIDIA's DGX Cloud team, he specializes in assisting customers with deploying their workloads at scale. Anshul has a strong background in SRE and has extensive experience in managing production-grade Kubernetes clusters across various Cloud Service Providers (CSPs). He has received Ph.D. in computer science from TU Munich, graduating summa cum laude.