We classify the AI & Data Science Platforms into two major categories — Integrated Machine Learning Platforms and AI Basic Software Platforms.

1. Integrated ML Platforms

Following the AI model development process, The Integrated ML Platforms integrate the tools for data preparation, model development, model training and deployment, etc.

The Integrated ML Platforms are committed to providing a one-stop "big and comprehensive" service. They offer both notebook and low-code programming interfaces. The latter mainly targets data analysts or business analysts who lack the AI knowledge. Integrated ML Platforms are often too complex and challenging to use.

Cloud service providers are one of the core players.

AWS Sagemaker: Amazon launched the Amazon SageMaker on November 2017, the pioneer of the global integrated machine learning platforms. The breadth and depth of Sagemaker's products are in the leading position in the industry.
Azure ML: Microsoft launched ML Studio (Classic Edition) — a no-code development environment. As the market and technology evolved, Microsoft improved the product features and created Azure Machine Learning, which provides complete lifecycle ML services. Now Azure ML has become one of the MLOps benchmark platforms.
AliCloud PAI: PAI was initially designed to serve Ali Group internally and was officially commercialized in 2018. PAI consists of four main sub-products: PAI-Studio low-code model development platform, PAI-DSW cloud-native interactive programming platform, PAI-DLC cloud-native AI foundation platform, and PAI-EAS cloud-native elastic inference service platform. PAI mainly focuses on model development, training and deployment.
Baidu BML: In 2020, Baidu officially released BML 4.0(short for BML). BML inherits the AI packages and libs from PaddlePaddle to provide a low-threshold, one-stop AI platform. Its core strengths are the rich algorithm libs and tools for professional AI developers accumulated in the open source platform. In addition, Baidu BML has broader integration with both Baidu Cloud and external data sources in Baidu Cloud.
Huawei ModelArts: In 2018, Huawei launched ModelArts 1.0. Like Sagemaker, ModelArts is dedicated to providing end-to-end ML services. ModelArts is intensely synergistic with Huawei's hardware and software ecology (Asend, CANN, MoXing, MindSpore, etc.) to improve computing performance. At the same time, it also has advantages in supporting rapid cloud-device-edge deployment.

2 AI BasicSoftware Platform

The AI Basic Software Platform is designed closely based on user requirements, allowing users to manage function configuration according to their needs . Compared with Integrated Machine Learning Platforms, AI foundational software platform tools are lighter and easier for data scientists and algorithm engineers.
In terms of product types, AI Basic Software Platforms are more abundant and diverse, with differentiated features and technical focus across products. Typical products include Databricks Deltalake Platform, Kubeflow, and Google Colab and JupyterLab, which are pure IDEs.

Among the products mentioned above, Kubeflow is worth mentioning. The open source community was founded in December 2017, and 2 years in the making, Kubeflow version 1.0 was officially released in March 2020. Based on Kubernetes, Kubeflow takes advantage of cloud-native technology to help algorithm developers accelerate AI development and deployment. Kubeflow is not a unified platform but a collection of loose tool components that can be used individually or in concert.

IDP (Intelligent Development Platform, launched by Baihai AI)also belongs to the AI Basic Software Platform category. IDP is a cloud-native, collaborative, performant AI development platform consisting of the easy-to-use IDE (IDP Studio)， high-performance computing engine(IDP Engine) and efficient data management system(IDP Ocean).