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    Machine Learning Platform for AI:Service architecture

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    Machine Learning Platform for AI:Service architecture

    Last Updated:Jun 21, 2023

    This topic describes the architecture of Machine Learning Platform for AI.

    Architecture

    The architecture of Machine Learning Platform for AI is divided into five layers, as shown in the preceding figure.

    1. Infrastructure layer: includes CPU, GPU, Field Programmable Gate Array (FPGA), and Neural network Processing Unit (NPU) resources.

    2. Computing engines and container services layer: includes MaxCompute, E-MapReduce (EMR), Realtime Compute, and Alibaba Cloud Container Service for Kubernetes (ACK).

    3. Computing framework layer: includes Alink, TensorFlow, PyTorch, Caffe, MapReduce, SQL, and Message Passing Interface (MPI). You can run distributed computing tasks in these frameworks.

    4. Machine Learning Platform for AI streamlines the workflows of machine learning, including data preparation, model creation and training, and model deployment.

      1. Data preparation: Smart labeling of Machine Learning Platform for AI allows you to label data and manage datasets in multiple scenarios.

      2. Model creation and training: Machine Learning Platform for AI provides diverse services to meet different modeling requirements. These services are Machine Learning Studio, Data Science Workshop (DSW), Deep Learning Containers (DLC), and AutoLearning. Machine Learning Studio is a service for visualized modeling. DSW allows you to create models by interactive programming. DLC is a cloud-native platform for training deep learning models. AutoLearning is a service for end-to-end automated model creation.

      3. Model deployment: Machine Learning Platform for AI provides Elastic Algorithm Service (EAS) and Blade to help you deploy models as services. EAS is a cloud-native online inference platform and Blade is a tool used to accelerate model inference. Machine Learning Platform for AI also provides an intelligent marketplace where you can obtain recommended solutions and model algorithms to solve business issues and improve production efficiency.

    5. Business layer: Machine Learning Platform for AI is widely used in finance, medical care, education, transportation, and security sectors. Search systems, recommendation systems, and financial service systems of Alibaba Group all use Machine Learning Platform for AI to explore data values for making informed business decisions.