A fundamental shift is currently taking place in how AI applications are built and deployed. AI applications are becoming more sophisticated and applied to broader use cases. This requires end-to-end AI lifecycle management--from data preparation, to model development and training, to deployment and management of AI apps. This approach can lower upfront costs, improve scalability, and decrease risk for customers using AI applications. While the cloud-native approach to app development can be appealing to developers, machine learning (ML) projects are notoriously time-intensive and cost-intensive, as they require a team with a varied skill set to build and maintain.

Nvidia has unveiled its Enterprise version 2.1, an update to the company's end-to-end artificial intelligence and machine learning workloads software. The updates affect the Nvidia TAO Toolkit and Nvidia Rapids, with further support being added for Red Hat OpenShift running in the public cloud. The company says this should "[make] enterprise AI even more accessible across hybrid or multi-cloud environments," with Microsoft Azure NVads A10 v5 series virtual machines also gaining certification. REST APIs integration, pre-trained weights import, TensorBoard integration, and new pre-trained models are some of the highlights coming to the latest iteration of Nvidia TAO Toolkit, version 22.05, which itself is a low code solution of Nvidia TAO. The tool is designed to make building computer vision and speech recognition models easier. New models, techniques, and data processing capabilities added to Nvidia RAPIDS 22.04 will provide "more support for data workflows," which will be available across all of the data science libraries.

Chintan Shah is a senior product manager at NVIDIA, focusing on AI products for intelligent video analytics. Chintan manages an end-to-end toolkit for efficient deep learning training and real-time inference. Previously, he developed hardware IPs for NVIDIA GPUs. Chintan holds a master's degree in electrical engineering from North Carolina State University.