This topic describes the documentation updates for new features and updates of Machine Learning Platform for AI (PAI).

July 2021

Date Feature Category Description References
2021-07-29 ASR models New feature The Chinese speech vectorization model and English speech vectorization model are added to Model Hub. ASR models
2021-07-06 Elastic Algorithm Service (EAS) SDKs New feature Official EAS SDKs are provided to call the services deployed based on models. EAS SDKs reduce the time required for defining the call logic and improves the call stability. PAI provides EAS SDKs for Python, Java, and Golang. SDK for Python, SDK for Java, and SDK for Go

June 2021

Date Feature Category Description References
2021-06-27 Plug-ins provided by AutoLearning Optimization The topics about how to use the computer vision model training plug-in and the general-purpose model training plug-in are updated based on the procedures in the PAI console. AI Industry Plug-In
2021-06-24 Model deployment by using custom images New feature During business development, environmental dependencies are often complex. If you use a processor to deploy a model as a service, you must package shared libraries to the processor. You cannot install the dependency to a path of the system by running the yum install command. This method is less flexible. Therefore, EAS provides a new feature that allows you to use a custom image to deploy a model as a service. Use a custom image to deploy a model service

May 2021

Date Feature Category Description References
2021-05-27 Authorization in EAS Optimization The sample code that shows the content of a RAM policy is updated. Grant permissions to RAM users
2021-05-20 Smart labeling based on the OCR template Optimization The procedure is updated. Smart labeling based on the OCR template

April 2021

Date Feature Category Description References
2021-04-25 AI computing asset management New feature This module unifies the management of PAI-related datasets, algorithms, models, and images. AI Computing Asset Management
2021-04-19 Product models New feature The product recognition model is added to ModelHub. Product recognition model
2021-04-07 Built-in processors New feature Built-in processors for TensorFlow 1.15 and PyTorch 1.6 are added. Built-in processors

March 2021

Date Feature Category Description References
2021-03-04 Offline prediction in end-to-end text recognition New feature EasyVision of PAI allows you to perform model training and prediction in end-to-end text recognition. You can use EasyVision to perform distributed training and prediction on multiple servers. This topic describes how to use EasyVision to achieve offline prediction in end-to-end text recognition based on existing training models. End-to-end text recognition
2021-03-04 Labeling templates New feature This topic describes labeling templates for text, videos, and images, and the scenarios and data structure of each labeling template. Labeling templates for images

February 2021

Date Feature Category Description References
2021-02-26 Learning path New feature This topic describes the learning path of PAI. Machine Learning Platform for AI
2021-02-25 Binary classification Optimization This topic describes the input parameters, PAI commands, and examples of algorithm components for binary classification. Linear SVM

January 2021

Date Feature Category Description References
2021-01-26 Intelligent video processing models New feature The models for general video classification and video highlights generation are added. This topic describes the input format and output format of both models, and provides test examples. Intelligent video processing models
2021-01-20 Distributed deep learning framework Whale New feature Whale is a flexible, easy-to-use, efficient, and centralized distributed training framework. It provides simple and easy-to-use API operations for data parallelism, model parallelism, pipeline parallelism, operator splitting, and hybrid parallelism that combines multiple parallelism strategies. Whale is developed based on TensorFlow and fully compatible with the TensorFlow API. You need only to add a few lines of code that describe distributed parallelism strategies to an existing TensorFlow model to perform distributed and hybrid parallel training. Quick start
2021-01-11 The development environment of Data Science Workshop (DSW) Optimization This topic describes how to work with the development environment of DSW, including how to use user interfaces, run preset cases, and manage third-party libraries. Work with the development environments of DSW
2021-01-11 Create a DSW instance Optimization You must create DSW instances before you use DSW to build Notebook models. This topic describes how to create a DSW instance. Create instances

December 2020

Date Feature Category Description References
2020-12-30 Overview of DSW editions New feature This topic describes the features, instance types, and supported zones of DSW editions. The editions are Individual Edition, GPU On-sale Edition, and Explorer Edition. Overview
2020-12-30 Image object detection New feature This topic describes how to use a trained model of EasyVision to perform offline object detection. Image object detection

November 2020

Date Feature Category Description References
2020-11-30 EAS Optimization You can use EAS to deploy a model as a RESTful API and then call the API by sending HTTP requests. EAS provides features such as auto scaling and blue-green deployment. These features allow you to use the online algorithm model service with high concurrency and stability at a low resource cost. EAS

October 2020

Date Feature Category Description References
2020-10-24 Object detection by using EasyVision New feature PAI provides EasyVision, which is an enhanced algorithm framework for visual intelligence. EasyVision provides a variety of features for model training and prediction. You can use EasyVision to train and apply computer vision models for your computer vision applications. This topic describes how to use EasyVision in DSW to detect objects. Use EasyVision to detect targets
2020-10-24 Online debugging by using WebIDE New feature This topic describes how to use WebIDE of DSW to debug the Python code in a notebook online. A sample notebook is provided by DSW. Use WebIDE to debug code online

September 2020

Date Feature Category Description References
2020-09-21 Smart labeling Optimization This topic describes how to label data. Smart labeling
2020-09-21 Billing of EAS Optimization This topic describes the billing rules for EAS of PAI. Billing of EAS

August 2020

Date Feature Category Description References
2020-08-25 Deep Learning Containers (DLC), a cloud-native platform where you can train deep learning models New feature This topic describes how to use the DLC platform to prepare for deep learning tasks and how to manage clusters and deep learning tasks. DLC
2020-08-14 Data preparation New feature This topic describes how to create datasets and label data. Data preparation
2020-08-14 Quick Start New feature This manual describes how to create an experiment in Machine Learning Studio. Quick Start
2020-08-10 Pricing Optimization This manual describes how to purchase services that are provided by PAI and the related billing rules for its services. Pricing

July 2020

Date Feature Category Description References
2020-07-22 Computer vision model training New feature You can label training data, train common computer vision models, and deploy models. Models that are developed on the mobile platform are optimized. You can test your model on your mobile phone by scanning the QR code of the model. Computer vision model training
2020-07-22 RAM user authorization Optimization If you want to manage instances and train models as a RAM user, you must first use your Alibaba Cloud account to grant permissions to the RAM user. Authorize RAM users
2020-07-22 Object Storage Service (OSS) authorization Optimization You must grant permissions to the OSS role that is assigned to AutoLearning before AutoLearning can assume this role to retrieve source data from OSS. OSS authorization