What Is ModelArts?

ModelArts is a one-stop AI development platform geared toward developers and data scientists of all skill levels. It enables you to rapidly build, train, and deploy models anywhere (from the cloud to the edge), and manage full-lifecycle AI workflows. ModelArts accelerates AI development and fosters AI innovation with key capabilities, including data preprocessing and auto labeling, distributed training, automated model building, and one-click workflow execution.

ModelArts covers all stages of AI development, including data processing, algorithm development, and model training and deployment. The underlying technologies of ModelArts support various heterogeneous computing resources, allowing developers to flexibly select and use resources. In addition, ModelArts supports popular open-source AI development frameworks such as TensorFlow, PyTorch, and MindSpore. ModelArts also allows you to use customized algorithm frameworks tailored to your needs.

ModelArts aims to simplify AI development.

ModelArts is suitable for AI developers with varying levels of development experience. Service developers can use ExeML to quickly build AI applications without coding. Beginners can directly use built-in algorithms to build AI applications. AI engineers can use multiple development environments to quickly compile code for modeling and application development.

Product Architecture

ModelArts supports the entire development process, including data processing, and model training, management, and deployment. It also provides AI Gallery for sharing models.

ModelArts supports various AI application scenarios, such as image classification, object detection, video analysis, speech recognition, product recommendation, and exception detection.

Figure 1 ModelArts architecture

Product Advantages

One-stop platform
The out-of-the-box and full-lifecycle AI development platform provides one-stop data processing, and development, training, management, and deployment of models.
Easy to use
- Multiple built-in models provided and free use of open-source models
- Automatic optimization of hyperparameters
- Code-free development and simplified operations
- One-click deployment of models to the cloud, edge, and devices
High performance
- The self-developed MoXing deep learning framework accelerates algorithm development and training.
- Optimized GPU utilization accelerates real-time inference.
- Models running on Ascend AI chips achieve more efficient inference.
Flexible
- Mainstream open-source frameworks such as TensorFlow, PyTorch, and MindSpore
- Mainstream GPUs
- Ascend chips
- Exclusive use of dedicated resources
- Custom images for custom frameworks and operators

Using ModelArts for the First Time

If you are a first-time user, the following information will help you get familiar with ModelArts:

Basic concepts
Basic Knowledge describes the basic concepts of ModelArts, including the basic process and concepts of AI development, and specific concepts and functions of ModelArts.
Getting started
Getting Started provides samples with detailed operations, helping you get started with ModelArts.
Best practices
ModelArts supports multiple open-source engines and provides extensive use cases based on the engines and functions. You can build and deploy models by referring to Best Practices.
Other functions and operation guides
- If you are a service developer, you can use ExeML to quickly build models without coding. For details, see User Guide (ExeML).
- If you are an AI engineer, you can use one or more functions in your AI development, including DevEnviron, data preparation, data labeling, model development, and inference. You can use one or more functions in your AI development.
- If you want to use ModelArts APIs or SDKs for AI development, see API Reference or SDK Reference.