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, 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.
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
Automatic optimization of hyperparameters
Code-free development and simplified operations
High performance
The self-developed MoXing deep learning framework accelerates algorithm development and training.
Models running on Ascend AI chips achieve more efficient inference.
Flexible
Mainstream open-source frameworks such as TensorFlow, PyTorch, and MindSpore
Ascend chips
Exclusive use of dedicated resources
Custom images for custom frameworks and operators