How to Self-Host and Hyperscale AI with Nvidia NIM

Nvidia NIMs are inference microservices that package up popular AI models along with all the APIs needed to run them at scale.
They include inference engines like tensor RT llm and data management tools for authentication, health checks, monitoring, etc.
These APIs and the model itself are containerized and run on Kubernetes, allowing deployment to the cloud, on-prem, or even on a local PC.
NIMs can be used to scale AI in any environment, augmenting human work rather than replacing it.
NIMs reduce development time while facilitating the deployment of tools that augment human capabilities.
NIMs can be accessed via the API and have been standardized to work with the OpenAI SDK.
They can also be pulled with Docker and run in a local environment or configured in the cloud to scale to any workload.

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