AI frameworks are software platforms that provide a set of tools, libraries, and features to facilitate the development, deployment, and management of AI applications. AI frameworks can help AI developers, researchers, and practitioners to create, train, test, optimize, and run AI models and algorithms with ease and efficiency. AI frameworks can also help AI users and consumers to access, interact, and benefit from AI solutions and services with convenience and confidence. AI frameworks can vary in terms of their scope, functionality, design, and popularity. Some AI frameworks are general-purpose and can support a wide range of AI tasks and domains, such as machine learning, deep learning, natural language processing, computer vision, speech recognition, etc. Some AI frameworks are specialized and can focus on a specific AI task or domain, such as natural language generation, image processing, reinforcement learning, etc. Some AI frameworks are open-source and can be freely used, modified, and distributed by anyone. Some AI frameworks are proprietary and can be owned, controlled, and licensed by a specific entity.