Building and deploying an Al-powered solution from idea to prototype to production is daunting. You need large volumes of data, Al expertise, and tools to curate, pre-process, and train Al models with the data. In addition, you need to optimize for inference performance and finally deploy AI into a usable, customer-facing application.

Infrastructure for Al deployments must be versatile to support diverse Al model architectures and multiple Al frameworks that can handle a variety of inference query types.

This whitepaper will give you a view of the end-to-end deep learning workflow and the details of taking Al-enabled applications from prototype to production deployments. It covers the evolving inference usage landscape, architectural considerations for the optimal inference accelerator, and the NVIDIA Al platform for inference.

Download the whitepaper today and get started on your AI development.

View: Deploying AI Models with Speed, Efficiency and Versatility: Inference on NVIDIA’s AI Platform