Systems | Development | Analytics | API | Testing

ClearML is now officially integrated into the NVIDIA TAO Toolkit 🎉. For those of you that don’t know yet, the NVIDIA TAO Toolkit, built on TensorFlow and PyTorch, is a low-code version of the NVIDIA TAO framework that accelerates the model training process by abstracting away the AI/deep learning framework complexity.

Enterprises who are actively increasing their AI maturity in a bid to achieve business transformations often find that with increased maturity comes increased complexity. For use cases that require very large datasets, the tech stacks required to meet business needs quickly become unwieldy.

In 2022, AI and ML came into the mainstream consciousness, with generative AI applications like Dall-E and GPT AI becoming massively popular among the general public, and ethical questions of AI usage stirring up impassioned public debate. No longer a side project for forward-thinking businesses or CEOs that find it intriguing, AI and ML are now moving towards the center of the business.

The IDC MarketScape: Worldwide Machine Learning Operations Platforms 2022 Vendor Assessment is an annual study that evaluates technology vendors based on a comprehensive framework. It provides an in-depth quantitative and qualitative assessment of MLOps solution vendors in a long-form research report, to help buyers make important technology decisions that will create long term business success.

The GigaOm Radar reports support leaders looking to evaluate technologies with an eye towards the future. In this year's Radar for MLOps report, GigaOm gave Iguazio top scores on multiple evaluation metrics, including Advanced Monitoring, Autoscaling & Retraining, CI/CD, and Deployment. Iguazio was therefore named a leader and also classified as an Outperformer for its rapid pace of innovation.

ClearML is an open source MLOps platform, and we love the community that’s been growing around us over the last few years. In this post, we’ll give you an overview of the structure of the ClearML codebase so you know what to do when you want to contribute to our community. Prefer to watch the video? Click below: First things first. Let’s take a look at our GitHub page and corresponding repositories. Later on, we’ll cover the most important ones in detail.