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Common Concepts of ModelArts

ExeML

ExeML is the process of automating model design, parameter tuning, and model training, model compression, and model deployment with the labeled data. The process is code-free and does not require developers to have experience in model development. A model can be built in three steps: labeling data, training a model, and deploying the model.

Device-Edge-Cloud

Device-Edge-Cloud indicates devices, intelligent edge nodes, and the public cloud.

Inference

Inference is the process of deriving a new judgment from a known judgment according to a certain strategy. In AI, machines simulate human intelligence, and complete inference based on neural networks.

Real-Time Inference

Real-time inference specifies a web service that provides an inference result for each inference request.

Batch Inference

Batch inference specifies a batch job that processes batch data for inference.

Ascend Chip

The Ascend chips are a series of Huawei-developed AI chips with high computing performance and low power consumption.

Resource Pool

ModelArts provides large-scale computing clusters for model development, training, and deployment. There are two types of resource pools: public resource pool and dedicated resource pool. The public resource pool is provided by default and is billed on pay-per-use basis. Dedicated resource pools must be purchased and are used exclusively.

AI Market

The AI market provides common models and algorithms. You can also share your own models or algorithms with other users or make them publicly available.

Parent topic: Basic Knowledge