Deploying Generative AI in Production with NVIDIA NIM

Unlock the potential of generative AI with NVIDIA NIM. This video dives into how NVIDIA NIM microservices can transform your AI deployment into a production-ready powerhouse.

Learn how NIM delivers flexible, scalable, and secure AI applications across any platform—cloud, data centers, or on-prem. Discover how its cloud-native architecture, backed by powerful tools like NVIDIA Triton Inference Server and TensorRT-LLM, simplifies the deployment and scaling of AI models, ensuring efficient and cost-effective operations. Whether you're looking to enhance security, reduce latency, or manage infrastructure costs, NVIDIA NIM provides the tools you need to deploy generative AI applications with confidence and control.

Dive into a quick 2-min overview on NVIDIA NIM and how it can scale generative AI deployment in the enterprise.

Overview

0:15 - Top Considerations for Scaling Generative AI in Production
0:34 - What are NVIDIA NIM accelerated microservices?
0:47 - Deploy locally with a single command
0:53 - Orchestrate an autoscale with Kubernetes
0:59 - Production Monitoring: Identity, Metrics, Health Check
1:07 - Inference engine powered by NVIDIA Triton Inference Server, NVIDIA TensorRT and TensorRT-LLM
1:20 - Use industry-standard APIs
1:28 - Streamline generative AI at scale

Developer resources

◻️ Get started today on ai.nvidia.com to simplify and speed up the deployment of production generative AI: https://www.nvidia.com/en-us/ai/

◻️ Getting Started Blog:
https://developer.nvidia.com/blog/nvi...

◻️ API Catalog: https://build.nvidia.com/explore/disc...

◻️ Join the NVIDIA Developer Program: https://nvda.ws/3OhiXfl

◻️ Read and subscribe to the NVIDIA Technical Blog: https://nvda.ws/3XHae9F

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